Abiotic stress : molecular genetics and genomics

Mukesh Jain, Rohini Garg, Rajeev K Varshney

2014

Frontiers Media SA

Abiotic stresses are the major cause that limits productivity of crop plants worldwide. Plants have developed intricate machinery to respond and adapt over these adverse environmental conditions both at physiological and molecular levels. Due to increasing problems of abiotic stresses, plant biotechnologists and breeders need to employ new approaches to improve abiotic stress tolerance in crop plants. Although current research has divulged several key genes, gene regulatory networks and quantitative trait loci that mediate plant responses to various abiotic stresses, the comprehensive understanding of this complex trait is still not available. This e-book is focused on molecular genetics and genomics approaches to understand the plant response/adaptation to various abiotic stresses. It includes different types of articles (original research, method, opinion and review) that provide current insights into different aspects of plant responses and adaptation to abiotic stresses.

Science (General), Botany

English

9782889193592

10.3389/978-2-88919-359-2

Syntax Warning: Invalid Font Weight
ABIOTIC STRESS: MOLECULAR
GENETICS AND GENOMICS
Topic Editors
Mukesh Jain, Rohini Garg
and Rajeev K. Varshney

PLANT SCIENCE

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ISSN 1664-8714
ISBN 978-2-88919-359-2
DOI 10.3389/978-2-88919-359-2

Frontiers in Plant Science

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December 2014  |  Abiotic Stress: Molecular Genetics and Genomics  |  1

ABIOTIC STRESS: MOLECULAR
GENETICS AND GENOMICS
Topic Editors:
Mukesh Jain, National Institute of Plant Genome Research (NIPGR), India
Rohini Garg, National Institute of Plant Genome Research (NIPGR), India
Rajeev K. Varshney, International Crops Research Institute for the Semi-Arid Tropics
(ICRISAT), India

Abiotic stresses are the major cause that limits productivity of crop plants worldwide. Plants
have developed intricate machinery to respond and adapt over these adverse environmental
conditions both at physiological and molecular levels. Due to increasing problems of abiotic
stresses, plant biotechnologists and breeders need to employ new approaches to improve
abiotic stress tolerance in crop plants. Although current research has divulged several key
genes, gene regulatory networks and quantitative trait loci that mediate plant responses
to various abiotic stresses, the comprehensive understanding of this complex trait is still
not available. This e-book is focused on molecular genetics and genomics approaches to
understand the plant response/adaptation to various abiotic stresses. It includes different
types of articles (original research, method, opinion and review) that provide current insights
into different aspects of plant responses and adaptation to abiotic stresses.

Frontiers in Plant Science

December 2014  |  Abiotic Stress: Molecular Genetics and Genomics  |  2

Table of Contents

04
06

10
15

25

32

50

62

74

91

Frontiers in Plant Science

Molecular Genetics and Genomics of Abiotic Stress Responses
Rohini Garg, Rajeev K. Varshney and Mukesh Jain
Genomics Strategies for Germplasm Characterization and the Development of
Climate Resilient Crops
Robert J. Henry
ß-catenin in Plants and Animals: Common Players but Different Pathways
Manisha Sharma, Amita Pandey and Girdhar K. Pandey
Tolerance to Drought and Salt Stress in Plants: Unraveling the Signaling
Networks
Dortje Golldack, Chao Li, Harikrishnan Mohan and Nina Probst
The Transcriptional Regulatory Network in the Drought Response and its
Crosstalk in Abiotic Stress Responses Including Drought, Cold and Heat
Kazuo Nakashima, Kazuko Yamaguchi-Shinozaki and Kazuo Shinozaki
Physiological and Genomic Basis of Mechanical-Functional Trade-Off in Plant
Vasculature
Sonali Sengupta and Arun Lahiri Majumder
Integrating Omic Approaches for Abiotic Stress Tolerance in Soybean
Rupesh Kailasrao Deshmukh, Humira Sonah, Gunvant Patil, Wei Chen, Silvas Prince,
Raymond Mutava, Tri Vuong, Babu Valliyodan and Henry T. Nguyen
Virus-Induced Gene Silencing is a Versatile Tool for Unraveling the Functional
Relevance of Multiple Abiotic-Stress-Responsive Genes in Crop Plants
Venkategowda Ramegowda, Kirankumar S. Mysore and Muthappa Senthil-Kumar
Comparative Phylogenomics of the CBL-CIPK Calcium-decoding Network in the
Moss Physcomitrella, Arabidopsis, and Other Green Lineages
Thomas J. Kleist, Andrew Spencley and Sheng Luan
Allele Diversity for Abiotic Stress Responsive Candidate Genes in Chickpea
Reference Set Using Gene Based SNP Markers
Manish Roorkiwal, Spurthi N. Nayak, Mahendar Thudi, Hari Deo Upadhyaya,
Dominique Brunel, Pierre Mournet, Dominique This, Prakash C. Sharma and Rajeev
K. Varshney

December 2014  |  Abiotic Stress: Molecular Genetics and Genomics  |  3

EDITORIAL
published: 21 August 2014
doi: 10.3389/fpls.2014.00398

Molecular genetics and genomics of abiotic stress
responses
Rohini Garg 1*, Rajeev K. Varshney 2,3 and Mukesh Jain 1
1

Functional and Applied Genomics Laboratory, National Institute of Plant Genome Research, New Delhi, India
International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
3
School of Plant Biology and Institute of Agriculture, The University of Western Australia, Crawley, WA, Australia
*Correspondence: rohini@nipgr.ac.in
2

Edited and reviewed by:
Richard A. Jorgensen, University of Arizona, USA
Keywords: abiotic stress, molecular genetics, genomics, functional genomics, regulatory networks, genetic diversity

Abiotic stresses are the major causes that limit productivity of
crop plants worldwide. Plants have developed intricate machinery
to respond and adapt over these adverse environmental conditions both at physiological and molecular levels. Due to increasing
abiotic stress constraints, plant biotechnologists and breeders
need to devise and employ new approaches to improve abiotic
stress tolerance in crop plants. Although the current research has
divulged several key genes, gene regulatory networks and quantitative trait loci (QTLs) that mediate plant responses to various
abiotic stresses, the comprehensive understanding of this complex trait is still not available. With an objective to understand
the plant response/adaptation to various abiotic stresses, a special issue was planned for the journal. The current research topic
“Abiotic Stress: Molecular Genetics and Genomics” has a combination of primary research articles, perspective, opinion and
review work, written by authorities in their respective fields.
These articles provide novel insights and detailed overviews on
the current knowledge into different aspects of plant responses
and adaptation to abiotic stresses.
The perspective article by Henry (2014) presents genomic
strategies for development of climate resilient crop varieties to
ensure food security. The discovery of genomic variations and
genes associated with climate adaptation found in wild relatives
of crop plants via whole-genome resequencing may be directly
relevant for implementing breeding approaches to develop environmentally adapted crops. In terms of understanding allelic variations, Roorkiwal et al. (2014) report allele diversity for 10 abiotic
stress-responsive genes in the reference set chickpea representing
the diversity of global chickpea germplasm. Detailed analysis provides haplotype network as well as estimates on genetic diversity
for candidate genes in the germplasm collection. The next article
by Deshmukh et al. (2014) highlights the importance of integration of various omics approaches for abiotic stress tolerance in
model legume crop, soybean. Significant genomic advances have
been made for abiotic stress tolerance in soybean in terms of
availability of molecular markers, QTL mapping, genome-wide
association studies (GWAS), genomic selection (GS) strategies,
and transcriptome profiling. It has been suggested that combining
QTL mapping based on GWAS along with transcriptome profiling can provide a valuable approach to identify candidate genes
involved in desired trait(s) (Deshmukh et al., 2014). It has been
realized that studies in other omics branches like proteomics,

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metabolomics and ionomics and their integration with genomics
are equally important and should be part of future research to
understand abiotic stress responses.
Two review articles (Golldack et al., 2014; Nakashima et al.,
2014) provide important insights into signaling mechanism and
transcriptional regulatory network, and their cross-talk in various
abiotic stress responses. Both of these articles highlight the central role of transcription factors (TFs) in abiotic stress response
and tolerance mechanisms. Other molecular signaling components, such as mitogen activated protein kinases (MAPKs), reactive oxygen species (ROS) and lipid-derived pathways have also
been implicated in plant adaptation to environmental adversity
(Golldack et al., 2014). In addition, the crucial role of β-cateninlike armadillo (ARM) proteins in abiotic stress responses has
also been anticipated (Sharma et al., 2014). The study of these
proteins can provide novel insights into the regulation of abiotic stress responses. Nakashima et al. (2014) suggested that TFs
function in crosstalk among various abiotic stress responses and
are being utilized to improve abiotic stress tolerance in different
crops. However, it is important to examine the molecular effects
of overexpression of TFs in addition to stress tolerance, because
their overexpression may affect other signaling pathways too. The
combing/pyramiding of transgenes for different stresses through
molecular breeding can provide superior lines with improved
stress tolerance in plants.
Calcium ions play a pivotal role in several signal transduction
cascades in plants especially abiotic stress signaling. Calcineurin
B-Like proteins (CBLs) function as calcium sensors and modulate the activity of CBL-Interacting Protein Kinases (CIPKs). The
CBL-CIPK network helps maintaining proper ion balances during abiotic stresses. The CBL and CIPK homologs are present
in all green lineages and phylogenomic analysis suggests their
expansion from a single CBL-CIPK pair present in the ancestor
of modern plants and algae (Kleist et al., 2014). The conservation of NAF domain and yeast two-hybrid results pointed the
presence of physically and functionally connected CBL-CIPK network in plants. It is intriguing to analyze the precise role of
CBL-CIPK pairs in abiotic stress responses. Virus-induced gene
silencing (VIGS) has emerged as an efficient and robust tool for
gene function analysis in plants. Ramegowda et al. (2014) provide an elegant overview of the usage of VIGS in different crop
species. The article covers recent advances, limitations and future

August 2014 | Volume 5 | Article 398 | 4

Garg et al.

prospects for characterization of abiotic stress related genes and
understanding abiotic stress tolerance mechanism. Sengupta and
Majumder (2014) addressed the mechanical-functional tradeoff in plant vasculature, which can have an adaptive value
under abiotic stress conditions. The authors have also provided
physiological and genomic basis of abiotic stress tolerance and
new possibilities for bridging physiology and genomics for crop
improvement.
In summary, the articles presented here emphasize the involvement of a variety of genes/pathways and regulatory networks in
abiotic stress responses. The broad-range of articles involving
genomics and breeding approaches deepen our existing knowledge about this complex trait. Further, despite the existing comprehensive knowledge in this area, many questions still remain
unaddressed. With the climate change threat, depletion of natural resources and ever increasing global population, sustainable
and higher crop production is greatly needed. Therefore, there is
an urgent need to employ various approaches and their integration to understand the molecular basis of abiotic stress response
and adaptation for the development of stress-tolerant crop
varieties.

REFERENCES
Deshmukh, R., Sonah, H., Patil, G., Chen, W., Prince, S., Mutava, R., et al. (2014).
Integrating omic approaches for abiotic stress tolerance in soybean. Front. Plant
Sci. 5:244. doi: 10.3389/fpls.2014.00244
Golldack, D., Li, C., Mohan, H., and Probst, N. (2014). Tolerance to drought and
salt stress in plants: unraveling the signaling networks. Front. Plant Sci. 5:151.
doi: 10.3389/fpls.2014.00151
Henry, R. J. (2014). Genomics strategies for germplasm characterization and
the development of climate resilient crops. Front. Plant Sci. 5:68. doi:
10.3389/fpls.2014.00068

Frontiers in Plant Science | Plant Genetics and Genomics

Abiotic stress: molecular genetics and genomics

Kleist, T. J., Spencley, A. L., and Luan, S. (2014). Comparative phylogenomics of the
CBL-CIPK calcium-decoding network in the moss Physcomitrella, Arabidopsis,
and other green lineages. Front. Plant Sci. 5:187. doi: 10.3389/fpls.2014.00187
Nakashima, K., Yamaguchi-Shinozaki, K., and Shinozaki, K. (2014). The transcriptional regulatory network in the drought response and its crosstalk in abiotic
stress responses including drought, cold, and heat. Front. Plant Sci. 5:170. doi:
10.3389/fpls.2014.00170
Ramegowda, V., Mysore, K. S., and Senthil-Kumar, M. (2014). Virus-induced gene
silencing is a versatile tool for unraveling the functional relevance of multiple abiotic-stress-responsive genes in crop plants. Front. Plant Sci. 5:323 doi:
10.3389/fpls.2014.00323
Roorkiwal, M., Nayak, S. N., Thudi, M., Upadhyaya, H. D., Brunel, D., Mournet,
P., et al. (2014). Allele diversity for abiotic stress responsive candidate genes in
chickpea reference set using gene based SNP markers. Front. Plant Sci. 5:248.
doi: 10.3389/fpls.2014.00248
Sengupta, S., and Majumder, A. L. (2014). Physiological and genomic basis of
mechanical-functional trade-off in plant vasculature. Front. Plant Sci. 5:224.
doi: 10.3389/fpls.2014.00224
Sharma, M., Pandey, A., and Pandey, G. K. (2014). β-catenin in plants and
animals: common players but different pathways. Front. Plant Sci. 5:143. doi:
10.3389/fpls.2014.00143
Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 14 July 2014; accepted: 25 July 2014; published online: 21 August 2014.
Citation: Garg R, Varshney RK and Jain M (2014) Molecular genetics and genomics
of abiotic stress responses. Front. Plant Sci. 5:398. doi: 10.3389/fpls.2014.00398
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Garg, Varshney and Jain. This is an open-access article distributed
under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s)
or licensor are credited and that the original publication in this journal is cited, in
accordance with accepted academic practice. No use, distribution or reproduction is
permitted which does not comply with these terms.

August 2014 | Volume 5 | Article 398 | 5

PERSPECTIVE ARTICLE
published: 25 February 2014
doi: 10.3389/fpls.2014.00068

Genomics strategies for germplasm characterization and
the development of climate resilient crops
Robert J. Henry*
Queensland Alliance for Agriculture and Food Innovation, University of Queensland, Brisbane, QLD, Australia

Edited by:
Rajeev K. Varshney, International
Crops Research Institute for the
Semi-Arid Tropics, India
Reviewed by:
Joseph F. Petolino, Dow
AgroSciences, USA
David Edwards, University of
Queensland, Australia
*Correspondence:
Robert J. Henry, Queensland Alliance
for Agriculture and Food Innovation,
University of Queensland, Brisbane,
QLD 4072, Australia
e-mail: robert.henry@uq.edu.au

Food security requires the development and deployment of crop varieties resilient to
climate variation and change.The study of variations in the genome of wild plant populations
can be used to guide crop improvement. Genome variation found in wild crop relatives may
be directly relevant to the breeding of environmentally adapted and climate resilient crops.
Analysis of the genomes of populations growing in contrasting environments will reveal
the genes subject to natural selection in adaptation to climate variations. Whole genome
sequencing of these populations should define the numbers and types of genes associated
with climate adaptation. This strategy is facilitated by recent advances in sequencing
technologies. Wild relatives of rice and barley have been used to assess these approaches.
This strategy is most easily applied to species for which a high quality reference genome
sequence is available and where populations of wild relatives can be found growing in
diverse environments or across environmental gradients.
Keywords: genomics, evolution, climate adaptation, crops, wild crop relatives

NEED TO ADAPT CROPS TO NEW AND CHANGING
ENVIRONMENTS AND THE ROLE OF GENOMICS
Agriculture needs significant increases in productivity to satisfy
the expected growth in demand for food in the next few decades.
The impact of climate variability and climate change on agricultural productivity is likely to be a major constraint to achieving
increased food production. This makes the development of crop
genotypes with resilience to climate change an important strategy for food security. Innovations in crop improvement based
upon application of advanced genomics tools may be a way to
address this need. The delivery of these technologies will require
significant efforts in coordinated development and delivery of
improved germplasm (Lybbert et al., 2013). Genomics allows
resources available for crop adaptation to environmental stress
to be characterized and utilized (Bansal et al., 2013). An evolutionary perspective may assist in the effective application of the
power of genomic tools to the development of climate resilient
crops adapted to a changing environment.
GENOMIC ANALYSIS OF CROP EVOLUTION AND
ADAPTATION TO CLIMATE CHANGE
Crop evolution has been relatively rapid under human selection
over the last 10,000 years of agriculture. However, it is built on a
very much longer period of evolution of wild crop relatives and
the plant groups from which they are sourced. Understanding the
processes and history of crop domestication and the evolution
of related wild species provides critical knowledge to guide the
development of crop varieties that are resilient to climate change
in the future.
Analysis of wild plant populations provides evidence of factors contributing to success in periods of climate change. For
example, hybridization between species may be an advantage
in adapting to rapid climate change by providing new genetic

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combinations to cope with new environmental circumstances.
Closely related species that can hybridize are more likely to survive than highly divergent species that cannot hybridize (Becker
et al., 2013). Analysis of the genetics of populations growing
across environmental gradients or from contrasting environments
may be used to identify how plant populations adapt to climate under natural selection (Cronin et al., 2007). Sampling
of populations at the same time over a long period of time
can also be used to monitor adaptation to climate change but
few sites have been sampled in the past in a way that allows
this type of analysis to be conducted. Establishment of long
term experiments of this type would be of great value. Recent
dramatic improvements in genome analysis tools due to rapid
advances in DNA sequencing technology make feasible research
that should deliver much greater understanding of the relationships between wild and domesticated plant populations (Henry,
2012, 2013).
Recent fossil evidence suggests early diversification of groups
of crop wild relatives such as the grasses (Prasad et al., 2011). The
climate resilience of domesticated rice populations may be related
to their evolutionary history. For example, expansion of the range
of climates to which crops are adapted will require the transfer
of genes from wild populations adapted to new environments or
the use of novel genes. Crop species are derived for many different
flowering plant groups but many are from a small number of families (e.g., Poaceae and Fabaceae). Crop plants have many traits that
reflect the environments in which they evolved prior to domestication. Humans have collected plants for food for a long period
of time prior to domestication of plants and the establishment of
agriculture in the last 10,000 years. Pre-domestication use of plants
by humans or natural variants that suit domestication (Ishii et al.,
2013) may have also impacted upon some plant populations but
domestication has usually resulted in significant genetic alteration

February 2014 | Volume 5 | Article 68 | 6

Henry

of plants to suit human production in agriculture and food uses
(Jin et al., 2008).

CHOICE OF SPECIES FOR CLIMATE RESILIENT AGRICULTURE
Domesticated crop species are few in number compared to the
total number of land plant species (Henry, 2010). A small number
of plant species that have been adapted to wide scale production
account for a large part of the energy and protein in human diets.
These have become the key crops contributing to global food security. A larger number of species have been domesticated for more
limited local production in specific regions. Some of these could
be considered for adaptation to a wider range of environments.
Genomics tools provide new options for accelerated domestication of new species to allow adaptation of agriculture to climate
change (Shapter et al., 2013).
MONO-PHYLETIC AND POLYPHYLETIC DOMESTICATION

Domestication may have been a single genetic event with all the
domesticated plants being descendent from the same wild parents
or have involved a few or many independent domestication events
with many wild plants contributing to the domesticated gene pool.
This understanding may provide the opportunity to repeat the
domestication of important crop species from a different or more
diverse gene pool. Genome analysis may be used to guide this
process.
CENTERS OF ORIGIN

The center of origin of a crop species is the region from which the
species is believed to have been domesticated. These are the environments that the crop plant was originally best adapted to survive
at the time of domestication. Domestication from a different population selected by genome analysis may provide an opportunity
to develop genotypes adapted to a new environment.
CENTERS OF DIVERSITY

Genome analysis allows rapid identification of geographic centers
of genome diversity. The center of diversity of a crop species is
the region displaying the greatest genetic diversity of the crop
species or its wild relatives. This may be distinct from the center
of origin as plant species may have been domesticated in areas
that are not those including the greatest diversity. Identification
of these locations may provide new and diverse germplasm and
define new environments for production of the crop now or in
the future. Asian rice (Oryza sativa) was probably domesticated in
China from wild O. rufipogon. The A genome clade of wild rice
relatives is now considered to be most diverse further south with a
center of diversity in New Guinea, Australia, and Indonesia. These
locations may prove to be good sources of novel germplasm for
rice improvement. Species from more temperate regions could be
used to adapt rice to production in cooler climates.
PRIMARY, SECONDARY, AND TERTIARY GENE POOLS

The gene pools of crop species may be considered at several levels.
Genomic analysis may have value at all of these levels. The primary
gene pool is the gene pool of the plant found in domestication
and usually the species from which the crop was domesticated.
The primary gene pool includes those plants that are available for
direct use in genetic improvement of the species. The secondary

Frontiers in Plant Science | Plant Genetics and Genomics

Genomics of climate resilient crops

gene pool may include more diverse material from other species
that can be accessed but with a greater degree of difficulty. This
often includes other species in the same or a related genus (Dillon
et al., 2007). The tertiary gene pool is a wider group of plants from
which genes can be accessed but only with significant difficulty
(e.g., plants in the family outside the genus that can be accessed
as a source of new genes but only with technological intervention). Understanding the genetic basis of domestication and the
issues associated with access of genes from more difficult (or distant) relatives facilitates their use in crop improvement and in
the domestication of new species to adapt agriculture to climate
change (Malory et al., 2011). These analyses are more powerful at
the whole genome level.

ADVANCES IN GENOMICS OF CROPS
Advances in DNA sequencing in the last few years have resulted in
genomic sequence data becoming more readily available (Edwards
et al., 2012). Major efforts have been made to produce reference
genome sequences for key species. This allows rapid analysis of
sequence variation within species. However, de novo assembly
of sequence data may be necessary to detect all differences and
advances in sequencing technology to make this routinely possible
with large plant genomes will be a significant advance.
Analysis of the genomes of plants growing along environmental
gradients may provide a greater understanding of how plants adapt
to climate variation under natural selection (Cronin et al., 2007;
Fitzgerald et al., 2011; Shapter et al., 2012).

GENOMIC ANALYSIS OF GENETIC RESOURCES
Analysis of the genomes of plant genetic resources will become a
key tool to enable their utilization in crop improvement for climate
adaptation. Targeting of genetic resources from environments that
match the one being breed for is an important strategy. Large
scale sequencing of accessions in plant germplasm collections will
provide a platform to enable these approaches (Henry, 2013).
Increased utilization of wild crop relatives will remain a major
strategy for adaptation of crops to the environmental factors associated with climate change. Many crop wild relatives remain poorly
collected and are not yet represent well in seed banks. Climate
change and human development risk loss of this genetic diversity making accelerated collection of crop wild relatives urgent.
Rice illustrates this challenge. The closest wild relatives of rice
are those from the A genome clade from which rice was domesticated (Vaughan et al., 2006). Recent research has identified two
possible new species in this group that represent important new
sources of diversity for rice improvement (Sotowa et al., 2013).
Rice wild relatives from some regions such as Africa (Wambugu
et al., 2013) and Australia (Henry et al., 2010) are poorly
known.

ANALYSIS OF NATURAL POPULATIONS AS A GUIDE TO
IMPROVEMENT OF CROPS FOR AGRICULTURAL PRODUCTION
The analysis of populations of wild relatives of barley (Cronin
et al., 2007; Fitzgerald et al., 2011) and rice (Fitzgerald et al., 2011;
Shapter et al., 2012) indicate the potential value of genome analysis
of these populations to support efforts to develop crop varieties
adapted to new climates.

February 2014 | Volume 5 | Article 68 | 7

Henry

In these studies, wild plants were collected from diverse environments or along a sharp environmental gradient. Sampling
of the same population over time as the climate changes could
be simulated by this strategy. In only a few cases we can access
samples that have been sampled from the same population over
a significant period of time. Key findings were that adaptation
to hotter or dryer environments was associated with increased
diversity of biotic stress genes. Coping with abiotic stress may
be confounded by overriding associated changes in the biotic
environment (Fitzgerald et al., 2011).

REMOVING THE CONSTRAINT OF END USE QUALITY ON
RAPID CROP ADAPTATION TO CLIMATE
Productivity gains in crop production require elimination of constraints to utilization of more diverse germplasm. In some species
the requirements of end uses are a major limitation. Market
requirements for specific food or processing attributes that are
complex or not well understood at the genetic level can greatly
hamper attempts to use diverse adapted germplasm. Genomics
tools that allow these traits to be readily selected for in breeding will assist by removing these as constraints to rapid climate
adaptation (Henry, 2014). Food quality traits are often associated
with human selection in domestication. They are often relatively
simply controlled genetically because of their relatively recent and
brief evolution under human selection in the last 10,000 years
or less. Improved understanding these genes can be targeted as
achievable steps toward removing a major constraint on climate
adaptation.
AVOIDING SELECTION THAT REDUCES CLIMATIC RESILIENCE
Human selection for quality may result in loss of environmental adaptation. Fragrance in rice is highly attractive to humans
and adds significant value to rice. The sequencing of the rice
genome allowed the identification of the genetic basis of this trait
(Bradbury et al., 2005) due to the gene being flanked by closely
linked known markers (Qingsheng et al., 2003). The gene responsible is an aldehyde dehydrogenase (Bradbury et al., 2008) the
activity of which is lost in fragrant genotypes. The loss of the gene
reduces the ability of the plant to cope with salt stress (Fitzgerald
et al., 2010). Whole genome understanding of genes responsible for quality (Kharabian-Masouleh et al., 2012) will allow their
relationship to abiotic stress tolerance genes to be carefully evaluated. Very attractive traits like fragrance may require strategies
such as selection of compensating abiotic stress tolerance genes to
counteract the deleterious effects of the quality gene.
DURABLE PEST AND DISEASE RESISTANCE IN A CHANGING
CLIMATE
The breeding of crops to cope with new pests and diseases will be
a key strategy to allow plants to cope with new climates. Genes
from wild populations will continue to be a major option but this
may need to be complemented by the use of novel transgenes or
genetic modifications.
ROLE OF CONTINUING TECHNOLOGY ADVANCES
Technology advances will continue to be critical. Ultimately we
need to be able to access whole genome information on all crop

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Genomics of climate resilient crops

species and their wild relatives to be effective in rapid crop adaptation to climate. Ongoing developments in the chemistry of DNA
sequencing and in information technology hardware and software
will be required to allow these very large amounts of information
to be captured and managed.

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B., et al. (2013). Hybridization may facilitate in situ survival of endemic
species through periods of climate change Nat. Clim. Chang. doi: 10.1038/
nclimate2027
Bradbury, L. M. T., Fitzgerald, T. L., Henry, R. J., Jin, Q., and Waters, D. L. E. (2005).
The gene for fragrance in rice. Plant Biotechnol. J. 3, 363–370. doi: 10.1111/j.14677652.2005.00131.x
Bradbury, L. M. E., Gillies, S. A., Brushett, D., Waters, D. L. E., and Henry, R. J. (2008).
Inactivation of an aminoaldehyde dehydrogenase is responsible for fragrance in
rice. Plant Mol. Biol. 68, 439–449. doi: 10.1007/s11103-008-9381-x
Cronin, J. K., Bundock, P. C., Henry, R. J., and Nevo, E. (2007). Adaptive climatic
molecular evolution in wild barley at the Isa defense locus. Proc. Nat. Acad. Sci.
U.S.A. 104, 2773–2778. doi: 10.1073/pnas.0611226104
Dillon, S. L., Shapter, F. M., Henry, R. J., Cordeiro, G., Izquierdo, L., and Lee, L.
S. (2007). Domestication to crop improvement: genetic resources for Sorghum
and Saccharum (Andropogoneae). Ann. Bot. 100: 975–989. doi: 10.1093/aob/
mcm192
Edwards, D., Henry, R. J., and Edwards, K. J. (2012). Advances in DNA sequencing accelerating plant biotechnology. Plant Biotechnol. J. 10, 621–622. doi:
10.1111/j.1467-7652.2012.00724.x
Fitzgerald, T. L., Shapter, F. M., McDonald, S., Waters, D. L. E., Chivers, I. H.,
Drenth, A., et al. (2011) Genome diversity in wild grasses under environmental stress. Proc. Nat. Acad. Sci. U.S.A. 108, 21139–21144. doi: 10.1073/pnas.
1115203108
Fitzgerald, T. L., Waters, D. L. E., Brooks, L. O., and Henry, R. J. (2010). Fragrance in
rice (Oryza sativa) is associated with reduced yield under salt treatment. Environ.
Exp. Bot. 68, 292–300. doi: 10.1016/j.envexpbot.2010.01.001
Henry, R. J. (2010). Plant Resources for Food, Fuel and Conservation. London:
Earthscan, 200.
Henry, R. J. (2012). Next generation sequencing for understanding and accelerating
crop domestication. Brief. Funct. Genomics 11, 51–56. doi: 10.1093/bfgp/elr032
Henry, R. J. (2013). Sequencing crop wild relatives to support the conservation and utilization of plant genetic resources. Plant Genet. Resour. doi:
10.1017/S1479262113000439
Henry, R. J. (2014). Wheat genomics for grain quality improvement. Cereal foods
world (in press).
Henry, R. J., Rice, N., Waters, D. L. E., Kasem, S., Ishikawa, R., Dillon, S. L.,
et al. (2010). Australian Oryza: utility and conservation. Rice 3, 235–241. doi:
10.1007/s12284-009-9034-y
Ishii, T., Numaguchi, K., Miura, K., Yoshida, K., Thien Thanh, P., Myint Htun, T.,
et al. (2013). OsLG1 regulates a closed panicle trait in domesticated rice. Nat.
Genet. 45, 462–465. doi: 10.1038/ng.2567
Jin, J., Huang, W., Gao, J.-P., Yang, J., Shi, M., Zhu, M.-Z., et al. (2008). Genetic
control of rice plant architecture under domestication. Nat. Genet. 40, 1365–1369.
doi: 10.1038/ng.247
Kharabian-Masouleh, A., Waters, D. L. E., Reinke, R. F., Ward, R., and
Henry, R. J. (2012). SNP in starch biosynthesis genes associated with nutritional and functional properties of rice. Sci. Rep. 2, 557, doi: 10.1038/
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Lybbert, T., Skerritt, J. H., and Henry, R. J. (2013). “Facilitation of future research and
extension through funding and networking support,” in Genomics and Breeding
for Climate-Resilient Crops, Vol. 1, Concepts and Strategies, ed. C. Kole (Heidelberg:
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Malory, S., Shapter, F. M., Elphinstone, M. S., Chivers, I. H., and Henry, R. J. (2011).
Characterizing homologues of crop domestication genes in poorly described wild
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9, 1131–1140. doi: 10.1111/j.1467-7652.2011.00640.x

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Henry

Prasad, V., Stromberg, C. A. E., Leache, A. D., Samant, B., Patnaik, R., Tang, L.,
et al. (2011). Late Cretaceous origin of the rice tribe provides evidence for early
diversification in Poaceae. Nat. Commun. 2, 480. doi: 10.1038/ncomms1482
Qingsheng, J., Waters, D. L. E., Cordeiro, G. M., Henry, R. J., and Reinke, R. F.
(2003). A single nucleotide polymorphism (SNP) marker linked to fragrance
in rice (Oryza sativa L.). Plant Sci. 165, 359–364. doi: 10.1016/S0168-9452(03)
00195-X
Shapter, F. M., Cross, M., Ablett, G., Malory, S., Chivers, I. H., King, G. J., et al.
(2013). High-throughput sequencing and mutagenesis to accelerate the domestication of Microlaena stipoides as a new food crop. PLoS ONE 8:e82641. doi:
10.1371/journal.pone.0082641
Shapter, F. M., Fitzgerald, T. L., Waters, D. L. E., McDonald, S., Chivers, I. H., and
Henry, R. J. (2012). Analysis of adaptive ribosomal gene diversity in wild plant
populations from contrasting climatic environments. Plant Signal. Behav. 7, 1–3.
doi: 10.4161/psb.19938
Sotowa, M., Ootsuka, K., Kobayashi, Y., Hao, Y., Tanaka, K., Ichitani, K., et al. (2013).
Molecular relationships between Australian annual wild rice, Oryza meridionalis,
and two related perennial forms. Rice 6, 26. doi: 10.1186/1939-8433-6-26
Vaughan, D. A., Ge, S., Kaga, A., and Tomooka, N. (2006). “Phylogeny and Biogeography of the Genus Oryza,” in Rice Biology in the Genomics Era, eds H.-Y. Hirano,
Y. Sano, A. Hirai, and T. Sasaki (Berlin: Springer), 218–234.

Frontiers in Plant Science | Plant Genetics and Genomics

Genomics of climate resilient crops

Wambugu, P., Furtado, A., Waters, D., Nyamongo, D., and Henry, R. (2013). Conservation and utilization of African Oryza genetic resources. Rice 6, 29. doi:
10.1186/1939-8433-6-29
Conflict of Interest Statement: The author declares that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 11 January 2014; accepted: 10 February 2014; published online: 25 February
2014.
Citation: Henry RJ (2014) Genomics strategies for germplasm characterization
and the development of climate resilient crops. Front. Plant Sci. 5:68. doi:
10.3389/fpls.2014.00068
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Henry. This is an open-access article distributed under the terms of the
Creative Commons Attribution License (CC BY). The use, distribution or reproduction
in other forums is permitted, provided the original author(s) or licensor are credited
and that the original publication in this journal is cited, in accordance with accepted
academic practice. No use, distribution or reproduction is permitted which does not
comply with these terms.

February 2014 | Volume 5 | Article 68 | 9

OPINION ARTICLE
published: 10 April 2014
doi: 10.3389/fpls.2014.00143

β-catenin in plants and animals: common players but
different pathways
Manisha Sharma , Amita Pandey and Girdhar K. Pandey*
Stress Signal Transduction Lab, Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
*Correspondence: gkpandey@south.du.ac.in
Edited by:
Mukesh Jain, National Institute of Plant Genome Research, India
Reviewed by:
Maik Boehmer, Westfälische-Wihelms-Universität Münster, Germany
Ashish Kumar Srivastava, Bhabha Atomic Research Centre, India
Keywords: beta-catenin, Armadillo, abiotic stress, Wnt signaling, U-box

INTRODUCTION
A key node in number of essential cellular processes in eukaryotes, Armadillo
was originally characterized in Drosophila
as the component of Wingless/Wnt
signal transduction pathway (NussleinVolhard and Wieschaus, 1980). β-catenin
is the mammalian homolog of Armadillo
playing dual role in structural and transcriptional regulation during embryonic
development (Conacci-Sorrell et al.,
2002). Even though initially characterized in animals, members of the
Armadillo proteins are also known to
exist in non-animals including slime
mold (Dictyostelium discoideum) and
plants (Wang et al., 1998; Barelle et al.,
2006; Veses et al., 2009). The existence
of Armadillo repeat family of proteins
across species suggests ancient evolutionary origin and functional conservation
of these proteins in multicellular organisms (Coates, 2003). The intricate role
of β-catenin raises several doubts about
the mechanism by which it mediates
interaction with diverse partner proteins using common interface, and how
this interaction influences adhesion and
transcription?
The ARM family proteins have been
identified with multiple functional
domains in more than one species.
Genome-wide studies in plants have
shown the existence of large number of
Armadillo homologs in Physcomitrella
patens, Arabidopsis and Oryza sativa
(Mudgil et al., 2004; Sharma et al., 2014).
One assumption is that, Armadillo family being evolutionary conserved, perform
similar role in all organisms. However, the
existence of multigene Armadillo family

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with various subfamilies indicate novel
species specific functions of these proteins
in plants. Several recent studies have made
known the function of numerous ARM
proteins in Arabidopsis and rice. Apart
from their analogous role in regulation of
gene expression and developmental processes, various proteins were discovered to
be predominantly involved in plant stress
responses.
Thus, an intriguing and important
question remains as in what way the
similar effector proteins of Wnt pathway function and how similar canonical
response is prevented or exist in plants.
Recent progress in studies of ARM proteins in plants has suggested some possible answers to this question. However,
the Wnt signaling mechanism regulated
by ARM repeat proteins is still unknown.
Regarding this, many underscoring questions are just beginning to emerge that
remains to be answered.

Wnt SIGNALING—DEVELOPMENTAL
REGULATION IN PLANTS AND
ANIMALS
Wnt proteins are one of the foremost signaling molecule essential for cell polarity,
embryonic development and the determination of cell fate in metazoa (Cadigan
and Nusse, 1997; Wodarz and Nusse,
1998; Logan and Nusse, 2004). A combination of molecular and genetic studies has provided evidences for how Wnt1,
Wnt3a, and Wnt8 specifically induce
the activation of “canonical β-catenin”
pathway in animals (Du et al., 1995;
Shimizu et al., 1997; Kuhl et al., 2000).
However, no evidence for a Wnt, Frizzled
(Fz) and low-density-lipoprotein-related

protein receptors has been obtained in
plants. Despite this, few homologs of
proteins, which act as negative regulator of Wnt signaling has been unveiled
in plants. Based on BLAST searches, the
serine/threonine kinase GSK-3 (glycogen
synthase kinase-3), CK1 (casein kinase 1)
and APC (Adenomatous polyposis coli),
which together form a destruction complex to stimulate degradation of β-catenin
in animals were found to be conserved
in plants (Figure 1) (Li et al., 2001). This
has been proven in animals that activity of GSK3/CK1 complex is inhibited in
response to Wnt signal perception at the
cell surface to relieve its inhibitory effects
on downstream β-catenin (He et al., 2004;
Tamai et al., 2004; Nusse, 2005). The conservation of β-catenin destruction complex in plants points toward novel targets
and modulation of Wnt signaling.

POTENTIAL “Wnt-LIKE” SIGNALING
FUNCTIONS FOR PLANT ARM FAMILY
PROTEINS
Arabidopsis comprises a multigene
SHAGGY-related protein kinase (ASK)
gene family, which is 70% identical to
glycogen synthase kinase-3 from mammals, (Bourouis et al., 1990; Siegfried
et al., 1990; Woodgett, 1990) classified into
four distinct subfamilies (Jonak and Hirt,
2002). In the past few years, significant
progress has been made in understanding how GSK3s perform their diverse
functions in plants. The diverged biological functions of these members in signal
transduction, cell patterning, cytokinesis
and determination of cell fate has been
established and credited to their diversity within plants (Dornelas et al., 1998).

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β-catenin in plants and animals

Sharma et al.

FIGURE 1 | Functional comparison of β-cat like-ARM repeats protein in
plants and animals. (A) Adhesion Complex: β-catenin in animals binds
cytoplasmic tail of cadherin to link it with α-catenin. Additionally, β-catenin
together with APC interacts with microtubule complexes. In plants,
ARK1/MRH2 (ARM repeat kinesin1/morphogenesis of root hair 1) interacts
with NEK6 (NIMA-related protein kinase 6) to mediate root epidermal cell
morphogenesis. CC represent coiled coil domain. (B) Destruction Complex:
β-catenin is targeted for proteasomal degradation by a GSK3, APC, CKI, and
Axin complex in the cytoplasm. Similarly in plants, ARM/U-box proteins, in

Most of the plants GSKs are found to
be involved in brassinosteroid signaling
and salt stress response (Dornelas et al.,
2000; Kim et al., 2009). Brassinosteroids
(BRs) are plant hormones, which signal
through a plasma membrane localized
receptor kinase BRI1. BRI1 interacts with
BAK1 (BRI1 associated receptor kinase 1)
to mediate plant steroid signaling (Nam
and Li, 2002). BES1 has been identified
as a suppressor of BRI1, which in turn
is negatively regulated by a kinase BIN2
(Yin et al., 2002). Interestingly, the BR
signaling pathway mechanism is analogous to the Wnt signaling pathway. In
the proposed model, BIN2 which shares
sequence homology with GSK-3 (Li and

response to various stimuli target substrate protein for proteasomal
degradation. (C) Transcriptional Complex: Wnt signals inhibits the destruction
complex, free β-catenin enters the nucleus where it links with the
transcriptional regulators to activate transcription of target genes. In plants,
ARIA an ARM protein with BTB/POZ domain binds with ABF2 and NEK6
transcription factors to stimulate transcription of ABA responsive genes.
Additionally, ARABIDILLO1/2 interacts with ASK2/11 through their F-box
domain to mediate degradation of possibly a positive regulator of GA3
signaling to promote transcription of genes related to lateral root development.

Nam, 2002), phosphorylate and destabilize its substrate BES-1. In response to
brassinosteroids, BES-1 is stabilized and
accumulates in the nucleus to activate
target gene expression (Yin et al., 2002).
It is important to note that both BES-1
and β-catenin does not share homology at
the protein sequence level. Similarly, BRI1
and Wnt are the two different receptors
and does not belong to the same family
(He et al., 2002; Yin et al., 2002; Zhao
et al., 2002). However, it will be interesting to know if any of the protein in
multigene Armadillo family in plants, gets
regulated in the same manner or it is
simply the way in which the pathway is
conserved.

Frontiers in Plant Science | Plant Genetics and Genomics

Meanwhile, several lines of evidence
suggest the role of Wnt signaling proteins i.e., Armadillo repeats containing
proteins in the developmental regulation
in both animals and plants (Amador
et al., 2001). p120ctn is an Armadillo
repeat protein identified as a component
of E-cadherin-catenin cell adhesion complex (Daniel et al., 2002). The signaling
and cell adhesion co-factor p120ctn is the
only known binding partner for Kaiso,
a novel BTB/POZ domain zinc finger
transcription factor (Daniel et al., 2002).
Another possible candidate mediating
interaction within actin and microtubule
filaments in plants is ARK/MRH2 kinesin
(ARM repeat kinesin/Morphogenesis of

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β-catenin in plants and animals

Sharma et al.

root hair). ARK/MRH2 interacts with
NIMA-related protein kinase NEK6, to
regulate epidermal cell morphogenesis by
modulating microtubule dynamics (Sakai
et al., 2008).
In relation to this, Arabidopsis
(AT5G13060) and rice (LOC_Os05G33050)
also possess homologous proteins comprising ARM repeats and a BTB/POZ
domain (Figure 1). The Arabidopsis
BTB/POZ ARM protein also known as
ABAP1 has been shown to be involved in
DNA replication and gene transcription
controls (Masuda et al., 2008).
Arabidillo-1/-2 and Oryzadillo are
the closest homolog of β-catenin in
Arabidopsis and Oryza sativa respectively,
consisting of an F-box motif near their
N-terminal, and several presumed sites
for GSK-3 phosphorylation (Gagne et al.,
2002; Kuroda et al., 2002; Coates, 2003).
Remarkably, Arabidillo’s are closest to the
β-catenin homolog in Dictyostelium’ Aar
protein that consists of an F-box domain
and is required for the differentiation
and expression of prespore specific genes
(Grimson et al., 2000). Besides, analogous to animals, physical interaction of
Arabidillo-1/-2 proteins through their
F-box domain with ASKs (SHAGGY-like
protein kinase) lead to the formation
of SCF complexes that target various
substrates for ubiquitn/26S proteasome–
mediated proteolysis has been proven
in plants (Changjun et al., 2010). This
suggest an evolutionary conservation of
signal transduction pathway elements and
their site of action within animals and
plants.

BEYOND Wnt SIGNALING: ROLE OF
PLANT ARM PROTEINS
Exposure to abiotic and biotic stress results
in alteration of cellular homeostasis in
plants. The first response to stress factors, is to activate the signal transduction
pathways that stimulate cell defense and
adaptive mechanisms. Ubiquitination is
a unique protein degradation mechanism
utilized by plants to effectively degrade
detrimental cellular proteins and components specific to these stress signalings.
A majority of U-box E3 ubiquitin ligase
encoding ARM proteins related to biotic
and abiotic stress have been identified in
plants. We can certainly anticipate new
insight into the molecular mechanism of

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plant β-catenin-like proteins function in
the context of abiotic stress signals.
There are 41 and 47 predicted
U-box/ARM proteins in the genome of
Arabidopsis and rice respectively (Mudgil
et al., 2004; Sharma et al., 2014). A few of
them have been functionally characterized
in Arabidopsis. Many of these proteins
have now been linked to specific stress and
hormonal responses.
A biological role for the U-box/ARM
protein AtPUB9 has been proposed in
ABA (Abscisic acid) signaling (Samuel
et al., 2008). In Arabidopsis, ATPUB18
and ATPUB19 are the two homologous
proteins. Molecular analysis of AtPUB19
showed that it is upregulated in response
to drought, salt, cold and ABA (Liu
et al., 2011). In the consecutive year,
role of ATPUB18 as a negative regulator
has been put forward in ABA-mediated
stomatal closure and drought responses
(Seo et al., 2012). A different homologous
pair of PUB proteins, AtPUB22 and 23
have been shown to play a combinatory
role in the negative regulation of drought
stress (Cho et al., 2008; Seo et al., 2012).
A closely related ortholog of ATPUB22/23
in Capsicum annum known as CaPUB1
was found to be highly inducible in
response to various abiotic stresses such as
drought, cold and salt (Cho et al., 2006).
Another report suggested the role of
AtCHIP, an Arabidopsis U-box/ARM protein in response to extreme temperature conditions. Subsequently, AtCHIP
was reported to be involved in the ABA
stress signaling pathway by mediating
interaction with protein phosphatase 2A
(Yan et al., 2003). In rice, SPL11 was
identified as a U-box containg ARM protein that functions as a negative regulator in the control of cell death and
pathogen defense (Zeng et al., 2004). The
Arabidopsis ortholog of SPL11, ATPUB13
is a functionally conserved protein regulating plant defense, cell death and flowering time (Li et al., 2012a,b). In Nicotiana,
two U-box/ARM proteins NtCMPG1 and
tobacco ACRE276 and their functional
homolog in Arabidopsis, AtPUB17 has
been implicated as positive mediators
of plant defense and stress signaling
(Gonzalez-Lamothe et al., 2006; Yang
et al., 2006). Apart from this, expression
analysis in rice has confirmed many of
the ARM proteins without any associated

domain to be differentially regulated
under abiotic stress conditions suggesting
a role of ARM repeats in the stress regulation (Sharma et al., 2014).
On the basis of facts described above,
it can be concluded that animal and plant
ARM repeat proteins share many resemblances. Therefore, it is possible that at
least some transcription effectors involved
in Wnt signaling are evolutionary conserved. These elements include nuclear
accumulation in response to extracellular
signal, phosphorylation and degradation.
Apart from the common response, plants
possess specific signaling pathways mediated by ARM proteins. In plants, ubiquitination is critically involved in the function of ARM proteins. The proliferation
of β-catenin-like ARM proteins in plants
suggest their significance in the regulation of diverse biological fuctions in them.
Further study of these proteins in plants
would contribute to our understanding of
the molecular factors involved in response
to abiotic stress.

ACKNOWLEDGMENTS
We are thankful to research grants from
Delhi University and Department of
Biotechnology (DBT), India.

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Conflict of Interest Statement: The authors declare
that the research was conducted in the absence
of any commercial or financial relationships
that could be construed as a potential conflict of
interest.
Received: 24 January 2014; accepted: 25 March 2014;
published online: 10 April 2014.
Citation: Sharma M, Pandey A and Pandey GK (2014)
β-catenin in plants and animals: common players but
different pathways. Front. Plant Sci. 5:143. doi: 10.3389/
fpls.2014.00143

This article was submitted to Plant Genetics and
Genomics, a section of the journal Frontiers in Plant
Science.
Copyright © 2014 Sharma, Pandey, and Pandey. This
is an open-access article distributed under the terms of
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The use, distribution or reproduction in other forums
is permitted, provided the original author(s) or licensor are credited and that the original publication in
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permitted which does not comply with these terms.

April 2014 | Volume 5 | Article 143 | 14

REVIEW ARTICLE
published: 22 April 2014
doi: 10.3389/fpls.2014.00151

Tolerance to drought and salt stress in plants: unraveling
the signaling networks
Dortje Golldack*, Chao Li, Harikrishnan Mohan and Nina Probst
Department of Biochemistry and Physiology of Plants, Faculty of Biology, Bielefeld University, Bielefeld, Germany

Edited by:
Mukesh Jain, National Institute of
Plant Genome Research, India
Reviewed by:
Peter Langridge, Australian Centre for
Plant Functional Genomics, Australia
Fan Chen, Institute of Genetics and
Developmental Biology – Chinese
Academy of Sciences, China
*Correspondence:
Dortje Golldack, Department of
Biochemistry and Physiology of
Plants, Faculty of Biology, Bielefeld
University, 33615 Bielefeld, Germany
e-mail: dortje.golldack@uni-bielefeld.de

Tolerance of plants to abiotic stressors such as drought and salinity is triggered by complex
multicomponent signaling pathways to restore cellular homeostasis and promote survival.
Major plant transcription factor families such as bZIP, NAC, AP2/ERF, and MYB orchestrate
regulatory networks underlying abiotic stress tolerance. Sucrose non-fermenting 1-related
protein kinase 2 and mitogen-activated protein kinase pathways contribute to initiation of
stress adaptive downstream responses and promote plant growth and development. As
a convergent point of multiple abiotic cues, cellular effects of environmental stresses are
not only imbalances of ionic and osmotic homeostasis but also impaired photosynthesis,
cellular energy depletion, and redox imbalances. Recent evidence of regulatory systems
that link sensing and signaling of environmental conditions and the intracellular redox status
have shed light on interfaces of stress and energy signaling. ROS (reactive oxygen species)
cause severe cellular damage by peroxidation and de-esterification of membrane-lipids,
however, current models also define a pivotal signaling function of ROS in triggering
tolerance against stress. Recent research advances suggest and support a regulatory
role of ROS in the cross talks of stress triggered hormonal signaling such as the abscisic
acid pathway and endogenously induced redox and metabolite signals. Here, we discuss
and review the versatile molecular convergence in the abiotic stress responsive signaling
networks in the context of ROS and lipid-derived signals and the specific role of stomatal
signaling.
Keywords: transcription factor, Arabidopsis, lipid signaling, ROS, drought, MAP kinase

INTRODUCTION
Survival of plants under adverse environmental conditions relies
on integration of stress adaptive metabolic and structural changes
into endogenous developmental programs. Abiotic environmental
factors such as drought and salinity are significant plant stressors
with major impact on plant development and productivity thus
causing serious agricultural yield losses (Flowers, 2004; Godfray
et al., 2010; Tester and Langridge, 2010; Agarwal et al., 2013). The
complex regulatory processes of plant drought and salt adaptation involve control of water flux and cellular osmotic adjustment
via biosynthesis of osmoprotectants (Hasegawa et al., 2000; Flowers, 2004; Munns, 2005; Ashraf and Akram, 2009; Agarwal et al.,
2013). Salinity induced imbalance of cellular ion homeostasis is
coped with regulated ion influx and efflux at the plasma membrane
and vacuolar ion sequestration (Hasegawa et al., 2000). Significantly, drought and salinity have additionally major detrimental
impacts on the cellular energy supply and redox homeostasis
that are balanced by global re-programming of plant primary
metabolism and altered cellular architecture (Chen et al., 2005;
Baena-González et al., 2007; Jaspers and Kangasjärvi, 2010; Miller
et al., 2010; Zhu et al., 2010). In this review we focus on recent
advances in understanding cellular signaling networks of biotechnological relevance in plant drought and salt adaptation. Here,
we focus on induced rather than intrinsic tolerance mechanisms
and do not explicitly distinguish between stress survival and tolerance. Known research findings on hormonal signal perception

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and transduction were integrated in the context of plant signaling networks under drought and salinity. We particularly aimed
on reviewing links of drought and salt induced signal transduction to plant hormonal pathways, metabolism, energy supply and
developmental processes.

PLANT HORMONES: PIVOTAL ROLES IN PLANT STRESS
SIGNALING
Plant hormones function as central integrators that link and reprogram the complex developmental and stress adaptive signaling
cascades. The phytohormone abscisic acid (ABA) functions as
a key regulator in the activation of plant cellular adaptation to
drought and salinity and has a pivotal function as a growth
inhibitor (Cutler et al., 2010; Raghavendra et al., 2010; Weiner
et al., 2010). Additionally, the view of function of ABA as a linking hub of environmental adaptation and primary metabolism is
increasingly emerging. Intriguingly, ABA triggers both transcriptional reprogramming of cellular mechanisms of abiotic stress
adaptation and transcriptional changes in carbohydrate and lipid
metabolism indicating function of ABA at the interface of plant
stress response and cellular primary metabolism (Seki et al., 2002;
Li et al., 2006; Hey et al., 2010).
Abscisic acid signals are perceived by different cellular receptors and a concept of activation of specific cellular ABA responses
by perception in the distinct cellular compartments is currently
emerging. The nucleocytoplasmic receptors PYR/PYL/RCARs

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(PYRABACTIN RESISTANCE/ PYRABACTIN RESISTANCELIKE/REGULATORY COMPONENT OF ABA RECEPTORS)
bind ABA and inhibit type 2C protein phosphatases (PP2Cs) such
as ABI1 and ABI2 (Ma et al., 2009; Park et al., 2009). Inactivation of PP2Cs activates accumulation of active SNF1-RELATED
PROTEIN KINASES (SnRK2s; Ma et al., 2009; Park et al., 2009;
Umezawa et al., 2009; Vlad et al., 2009). The SnRK2s regulate ABA-responsive transcription factors including AREB/ABFs
[ABA-RESPONSIVE PROMOTER ELEMENTS (ABREs) BINDING FACTORS (ABFs)] and activate ABA-responsive genes and
ABA-responsive physiological processes (Umezawa et al., 2009;
Vlad et al., 2009). Recently, function of plasma membranelocalized G protein-coupled receptor-type G proteins (GTGs) as
ABA receptor in Arabidopsis has been shown (Pandey et al., 2009).
Binding of ABA by GTG1/GTG2 and ABA hyposensitivity of
GTG1/GTG2 Arabidopsis loss of function mutants supported a
function of GTG1 and GTG2 as membrane-localized ABA receptors (Pandey et al., 2009). Extending the concept of involvement
of GTG1 and GTG2 in ABA signaling, a role of the proteins in
growth and development of Arabidopsis seedlings and in pollen
tube growth by function as voltage-dependent anion channels
has been reported (Jaffé et al., 2012). Thus, linking and dynamic
integration of GTG1 and GTG2 in cellular ABA signaling and
developmental regulation seems likely. Intriguingly, evidence for
a third pathway of ABA perception has been emerging with
the H subunit of Mg-chelatase (CHLH/ABAR). Integration of
CHLH/ABAR in the cellular ABA signaling cascade as a chloroplastic ABA receptor and by plastid-to-nucleus retrograde signaling
via the ABA responsive nucleocytoplasmic transcription repressor WRKY40 has been reported (Shen et al., 2006; Shang et al.,
2010; Du et al., 2012). These findings strongly suggest contribution of a chloroplast-localized pathway to modulate cellular
ABA signaling (Shen et al., 2006; Shang et al., 2010; Du et al.,
2012).
Currently, increasing evidence has been emerging for modulation of ABA-mediated environmental signaling by interaction
and competition with hormonal key regulators of plant cellular developmental and metabolic signaling. The complex and
divergent endogenous and exogenous signals perceived by plant
cells during development and environmental adversity are linked
and integrated by distinct and interactive hormonal pathways.
Particularly, convergence and functional modulation of ABA signaling by the plant growth regulating phytohormones gibberellic
acid (GA) has a key regulatory function in the plant cellular
network of stress and developmental signaling (Golldack et al.,
2013). According to accepted concepts, in Arabidopsis GA signaling is mediated by binding of GA to GID1a/b/c that are GA
receptor orthologs of the rice GA receptor gene OsGID1 (GA
INSENSITIVE DWARF 1; Ueguchi-Tanaka et al., 2005; Griffiths
et al., 2006; Feng et al., 2008). GA responsive GRAS [for GA
Insensitive (GAI), REPRESSOR of ga1-3 (RGA), SCARECROW
(SCR)] transcription factors function as major regulators in plant
GA-controlled development. Cellular accumulation of the GRAS
protein subgroup of DELLA proteins (GAI, RGA, RGL1, RGL2,
RGL3) represses GA signaling and restrains growth and development (Cheng et al., 2004; Tyler et al., 2004; Yu et al., 2004).
Interaction of DELLA proteins with the GA receptor GID1 induces

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Drought, salt and signaling

degradation of the DELLA proteins and activates the function of
GA (Cheng et al., 2004; Tyler et al., 2004; Yu et al., 2004). GA signals mediate binding of DELLA proteins to GID1 that is followed
by conformational conversion of DELLA proteins. The modified DELLAs are recognized by the the F-box protein SLEEPY1
(SLY1) in Arabidopsis (Silverstone et al., 2001, 2007; Fu et al.,
2002; Sasaki et al., 2003; Dill et al., 2004). Subsequently, DELLAs
are polyubiquitinated by the SCFSLY1/GID2 ubiquitin E3 ligase
complex and degraded via the 26S proteasome pathway (Silverstone et al., 2001; Fu et al., 2002; Sasaki et al., 2003; Dill et al.,
2004).
A linking function of DELLA proteins at the interface of
ABA-mediated abiotic stress responses and GA-controlled developmental signaling has been supported by modified salt tolerance
of the quadruple DELLA mutant with functional losses of rga, gai,
rgl1, and rgl2 (Achard et al., 2006). Interestingly, the RING-H2
zinc finger factor XERICO regulates tolerance to drought and ABA
biosynthesis in Arabidopsis (Ko et al., 2006). In addition, XERICO
is a transcriptional downstream target of DELLA proteins indicating function of XERICO as a node of plant abiotic stress responses
and development by linking GA and ABA signaling pathways (Ko
et al., 2006; Zentella et al., 2007; Ariizumi et al., 2013).
Recently, interesting evidence has been also provided for a
convergence and crosstalk of GA and ABA signaling with the
developmental regulator jasmonate in plant responses to drought.
Jasmonates are membrane-lipid derived metabolites that originate
from linolenic acid and have signaling functions in plant growth
and biotic stress responses (e.g., Wasternack, 2007; Wasternack
and Hause, 2013). Drought-induced transcriptional regulation of
the rice JA receptor protein OsCOI1a (CORONATINE INSENSITIVE 1) and of key regulators of JA signaling OsJAZ (jasmonic
acid ZIM-domain proteins) indicate significant integration of JA
metabolism and signaling in plant abiotic stress responses (Du
et al., 2013a; Lee et al., 2013). Importantly, expression of the
DELLA protein RGL3 responds to JA, and additionally RGL3 interacts with JAZ proteins (Wild et al., 2012). These recent research
advances emphasize function of DELLAs as an interface of ABA,
GA and jasmonic acid signaling and suggest pivotal functional
involvement of lipid-derived signaling in abiotic stress responses
(Figure 1).

MAJOR PLANT TRANSCRIPTION FACTOR FAMILIES: KEY
PLAYERS IN THE REGULATORY NETWORKS UNDERLYING
PLANT RESPONSES TO ABIOTIC STRESS
Comprehensive research on diverse abiotic stress responsive transcription factors shed light on the cellular mechanisms defining
plant environmental adaptation (Golldack et al., 2011). Significantly, the majority of ABA-regulated genes share the conserved ABA-responsive cis element (ABRE; Yamaguchi-Shinozaki
and Shinozaki, 2005, 2006). Besides the AREB/ABF (ABAresponsive element binding protein/ABRE-binding factor) family,
the DREB/CBF subfamily of the AP2/ERF transcription factors
has a central function in regulating plant adaptation to adversity
via ABA dependent and independent pathways (YamaguchiShinozaki and Shinozaki, 2005, 2006). Significant evidence for
a linking function of DREB/CBF in integrating environmentally derived signals and plant development was early provided

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Golldack et al.

Drought, salt and signaling

FIGURE 1 | Proposed model on crosstalk of abscisic acid (ABA), gibberellic acid (GA), and jasmonate signaling in plant cellular responses to the
abiotic stressors drought and salt. Hypothesized links are illustrated with dashed lines. The lines and arrows illustrate pathways that are not shown and
described in detail. Compare text for details.

by DREB/CBF overexpressing Arabidopsis with increased tolerance to drought, salt, and cold that was counterbalanced by
serious developmental defects (Kasuga et al., 1999). Supporting this functional connection, cold responsive CBF1 regulated GA biosynthesis and accumulation of the DELLA protein
RGA thus suggesting integration of AP2/ERF in abiotic stress
signaling and GA-regulated plant development (Achard et al.,
2008). The bZIP-type AREB/ABF transcription factors AREB1,
AREB2, and AREB3 target cooperatively ABRE-dependent gene
expression via a suggested interaction with the sucrose nonfermenting 1-related protein kinase 2 (SnRK2) protein kinase
SRK2D/SnRK2.2 (Yoshida et al., 2010). In addition, the Arabidopsis transcription factor bZIP24 controls reprogramming of
a broad array of salinity dependent and developmental gene
expression indicating a pivotal role of the factor in maintaining plant development under conditions of adversity (Yang et al.,
2009).

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The view of an integrative function of many transcription
factors in linking and balancing related or seemingly unrelated
cellular responses is further supported by other drought and
salt responsive transcription factors. Intriguingly, the picture is
increasingly emerging that plant signaling does not function as
independent and paralleled pathways but cellular crosstalks and
hubs within the signaling network exist. The view is increasingly emerging that stress adaptive signaling is tightly linked to
the cellular primary metabolism, energy supply and developmental processes. Thus, the tomato NAC-type (NAM, ATAF1,2,
CUC2) transcription factor SlNAC1 was responsive to multiple
abiotic and biotic stresses (Ma et al., 2013). Regulation of the
factor by ABA, methyl jasmonate, gibberellin, and ethylene indicates a node role of the factor in diverse signal transduction
pathways in tomato (Ma et al., 2013). The ABA-responsive NACtranscription factor VNI2 (VND-INTERACTING1) is a repressor
of xylem vessel formation and has additional functions in leaf

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Golldack et al.

aging thus integrating plant senescence to ABA signaling (Yang
et al., 2011). As another example, the NAC transcription factor
ANAC042 (JUB1, JUNGBRUNNEN 1) links leaf senescence to
hyperosmotic salinity response and is involved in H2 O2 signaling (Wu et al., 2012). Over-expression of the drought and ABA
responsive rice NAC-type transcription factor OsNAC10 allowed
identification of NAC dependent target genes that included AP2
and WRKY-type transcription factors (Jeong et al., 2010). These
findings strongly indicate a hub role of NAC transcription factors
in stress relevant hierarchic regulatory pathways.
Drought and ABA-responsive NAC factors are likely to control and link subclusters of cellular stress adaptation processes
under control of diverse subsets of specific transcription factors
such as members of the AP2 and WRKY families. Thus, hypersensitivity to drought of an Arabidopsis WRKY63 loss of function
mutant was related to reduced ABA sensitivity in guard cells indicating specific control of abiotic stress adaptation by this WRKY
transcription factor (Ren et al., 2010). ABA and salt responsive
Arabidopsis WRKY33 downstream targets genes with functions in
detoxification of reactive oxygen species (ROS) such as glutathione
S-transferase GSTU11, peroxidases, and lipoxygenase LOX1 (Jiang
and Deyholos, 2009). According to the involvement of WRKY33 in
osmotic stress responses, ROS detoxification and ROS scavenging,
a role of WRKY controlled cellular ROS levels in abiotic stress signaling seems likely. Extending and supplementing this concept, the
WRKY-type transcription factor ThWRKY4 from Tamarix hispida
controls cellular accumulation of ROS via regulating expression
and activity of antioxidant genes such as superoxide dismutase and
peroxidase (Zheng et al., 2013). Modified tolerance of ThWRKY4
overexpressing plants to salt and oxidative stress was referred to
ThWRKY4-mediated cellular protection against toxic ROS levels
(Zheng et al., 2013). Accordingly, an involvement of WRKY in
linking osmotic and oxidative stress defense as well as in ROS
mediated signaling crosstalks is suggested.
Another crucial and undervalued mechanism of plant adaptation to drought and salinity is the maintenance of cell wall
development and generation of the extracellular matrix in terms of
plant development and of protection against water loss. Intriguingly, transcriptional expression of the Arabidopsis R2R3-MYB
transcription factor AtMYB41 was induced by drought, salt,
and ABA (Cominelli et al., 2008; Lippold et al., 2009). Modified drought sensitivity of AtMYB41 overexpressing Arabidopsis
was linked to lipid metabolism, cell wall expansion, and cuticle deposition demonstrating a key function of AtMYB41 in plant
drought protection and survival via primary lipid metabolism and
cuticle formation (Cominelli et al., 2008). Recently, function of
AtMYB41 was also linked to primary carbon metabolism indicating a relationship between cuticle deposition, plant tolerance
against desiccation as well as cellular lipid and carbon metabolism
(Cominelli et al., 2008; Lippold et al., 2009). The salt-responsive
rice R2R3-type MYB transcription factor OsMPS (MULTIPASS)
targets genes with function in biosynthesis of phytohormones
and of the cell-wall (Schmidt et al., 2013a). These recent research
advances highlight the importance of a functional plant extracellular matrix and of cuticular polymer biosynthesis for plant
salt and drought adaptation. Accordingly, a key function of stress
responsive transcription factors in integrating cuticle formation

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Drought, salt and signaling

in the cellular primary metabolism in response to environmental
adversity is supported and likely.

LIPIDS: STILL AN ENIGMA IN ABIOTIC STRESS ADAPTATION
AND STRESS DERIVED SIGNALING?
Plant adaptation to a changing water and ionic status in the
surrounding environment requires rapid and sensitive sensing
of the stress situation and stress induced signaling. A crucial
and existential challenge for plant cells is the maintenance of
integrity of cellular membranes both at the plasma membrane
and of the enodomembranes. Thus, plants ensure homeostasis
of metabolism and cellular energy supply. Additionally, increasing evidence for pivotal involvement of lipid-derived signaling
in primary sensing of environmental changes and in triggering
and regulating cellular hormonal signaling cascades has been
emerging (Figure 1). Interestingly, vice versa ABA transcriptionally downstream targets lipid metabolism and lipid transfer
proteins suggesting tight interaction of ABA-dependent signaling
and lipid metabolic pathways to maintain structure and function of cellular membranes (Seki et al., 2002; Li et al., 2006).
Thus, ABA-triggered modification of primary lipid metabolism
contributes unequivocally to stress adaptive reorganization of
membranes and to the maintenance of cellular energy supply
under abiotic stress conditions and limitation in water supply.
Increased transpirational water loss of Arabidopsis mutants with
a functional knock out of LTP3 (Lipid Transfer Protein 3) suggests lipid-based adaptive changes of membranes and the plant
cuticle to regulate water loss and transpiration under drought
(Guo et al., 2013).
Drought-induced changes of monogalactosyldiacylglycerol
(MGDG) and digalactosyldiacylglycerol (DGDG) contents in the
chloroplast envelope and in thylakoid membranes in cowpea
(Vigna unguiculata) have been suggested to stabilize and maintain
lamellar bilayer structure and thus the function of chloroplasts
under drought stress (Torres-Franklin et al., 2007). In support of
these findings, changes of MGDG in the drought tolerant resurrection plant Craterostigma plantagineum during desiccation are
likely to contribute to membrane stabilization and to the maintenance of photosynthetic energy supply (Gasulla et al., 2013). The
Arabidopsis cold-responsive SFR2 (SENSITIVE TO FREEZING
2) mediates removal of monogalactolipids from the chloroplast
envelope membrane and stabilizes membranes during freezing
indicating that structural re-shaping of chloroplast membranes is
an essential and general mechanism of plant cellular dehydration
responses (Moellering et al., 2010).
Next to strong evidences for a fundamental importance of
lipid mediated re-organization of cellular membranes to cope
with changes in the plant water status, also comprehensive evidence for functions of lipid signaling in plant drought and salt
responses has been emerging. In rice, levels of PIP2 (phosphatidylinositol bisphosphate), PA (phosphatidic acid), and
DGPP (diacylglycerolpyrophosphate) increased upon salt stress
(Darwish et al., 2009). Based on these findings involvement of
phospholipase C and diacylglycerol kinase in salt stress induced
signaling has been hypothesized (Darwish et al., 2009). Function
of phospholipase C was linked to ABA signaling and stomatal
regulation indicating a functional role of phosphoinositides in

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Golldack et al.

guard cell signaling (Hunt et al., 2003; Mills et al., 2004). The
inositol phosphate myo-inositol hexakisphosphate (InsP6) has
a role as an ABA-responsive signaling molecule that regulates
stomatal closure via cellular calcium and the plasma membrane
potassium conductance (Lemtiri-Chlieh et al., 2003). Phosphoinositides have key roles in regulating membrane peripheral
signaling proteins and influence the activity of integral proteins
and ion channels (Suh et al., 2006; Falkenburger et al., 2010).
Importantly, work on inhibitors of phosphoinositide-dependent
phospholipases C (PI-PLCs) in Arabidopsis has provided considerable insight in the drought stress related lipid signaling by
identifying links of phosphoinositides to the DREB2 pathway
(Djafi et al., 2013).
A role of lipid-derived messengers in ABA signaling was
also evident by ACBP1 (acyl-CoA-binding protein 1) regulated
expression of PHOSPHOLIPASE Dα1 (PLDα1; Du et al., 2013b).
PHOSPHOLIPASE Dα1 has a function in the biosynthesis of the
ABA regulating lipid messenger PA indicating that modulation of
cellular lipid profiles is essential for regulation of abiotic stress
related ABA signaling (Du et al., 2013b; Jia et al., 2013; Lu et al.,
2013).

SnRK2 AND MAPK: ANOTHER CHAPTER IN PLANT ABIOTIC
STRESS SIGNALING
Protein kinases of diverse types and families are central integrators of plant abiotic stress signaling that link cellular metabolic
signaling to stress adaptive physiological processes as regulation
of ionic and osmotic homeostasis and to concerted changes of
ROS in stressed plant cells (Figure 1). Accepted models emphasize hub functions of yeast sucrose non-fermenting 1 (SNF1)
serine-threonine protein kinase, homologous mammalian AMPactivated protein kinase (AMPK) and plant SnRKs [Snf (sucrose
non-fermenting)-1-related protein kinases] in the cellular carbon
and energy metabolism (Halford and Hey, 2009). In plants, SnRK1
subgroup kinases have reported functions in metabolic signaling
and development (Zhang et al., 2001; Halford et al., 2003). Considerable insight into protein kinase functions in plant abiotic stress
adaptation has been provided by elucidation of the SOS pathway with central functions in maintenance and regulation of ion
homeostasis under salt stress. Intriguingly, the SnRK3 SOS2-like
(Salt Overly Sensitive3) protein kinases interact with SOS3like calcium-binding proteins to activate the plasma membrane
Na+ /H+ antiporter SOS1 via the SOS pathway (Chinnusamy et al.,
2004; Du et al., 2011). Recent research highlights direct interaction
of SnRK2.8 and the ABA responsive NAC (NAM/ATAF1/2/CUC2)
transcription factor NTL6 indicating integration of a SnRK2type kinase in the ABA controlled cellular framework of abiotic
stress adaptation (Kim et al., 2012). Extending these findings, in
rice, the SnRK2 kinase SAPK4 links regulation of ion homeostasis to scavenging of ROS thus suggesting interaction of ionic
and oxidative stress signaling pathways in plant adaptation to
adversity (Diédhiou et al., 2008). Consistent with these findings, a node function of SnRK2-type kinases in ABA signaling
and ROS generation has been elucidated in stomatal guard cells.
The ABA responsive SnRK2 OST1 (OPEN STOMATA 1) regulates stomatal closure by modulating the cellular production of
H2 O2 via NADPH oxidases (Sirichandra et al., 2009; Vlad et al.,

www.frontiersin.org

Drought, salt and signaling

2009). Arabidopsis OST1 mutants provided evidence for a role of
OST1 in the regulation of inward K+ channels, Ca2+ -permeable
channels and the slow anion channel SLAC1 thus supporting a
hub function of OST1 in linking ABA, ion channels and NADPH
oxidases in the regulation of stomatal apertures in guard cells
(Sirichandra et al., 2009; Vlad et al., 2009; Acharya et al., 2013). As
a fascinating finding, the Arabidopsis snrk2.2/2.3/2.6 triple-mutant
with decreased sensitivity to ABA allowed identification of SnRK2
phosphorylation targets that included proteins with functions in
chloroplasts, in signal transduction and in the regulation of flowering (Wang et al., 2013). These research advances provide insights in
SnRK2-mediated regulatory crosstalks and interactions of developmental, metabolic and stress adaptive processes in the plant
cellular signaling framework.
Recent advances on mitogen-activated protein kinase (MAPK)
mediated signal transduction cascades have provided another pivotal understanding of the integration of physiological and cellular
responses to environmental adversity. MAPK cascades functionally link MAP3Ks (MAP2K kinase) serine/threonine kinases,
MAP2K (MAPK kinase) dual-specificity kinases and MAPK serine/threonine kinases (Colcombet and Hirt, 2008). As an accepted
concept of functional importance in abiotic stress adaptation,
involvement of MAPKs in drought and salt adaptation have been
reported for wide ranging plant species such as rice, Arabidopsis to
alfalfa SIMK and SIMKK (Kiegerl et al., 2000; Ning et al., 2010; Yu
et al., 2010). Recent research highlights a central role of Arabidopsis MKK4 in the osmotic stress response by regulation of MPK3
activity, accumulation of ROS and targeting the ABA biosynthetic
process via NCED3 (NINE-CIS-EPOXYCAROTENOID DIOXYGENASE 3; Kim et al., 2011). Several studies indicated a hub
function of MPK6 as another member of the MAPK cascade in
linking of osmotic stress responses to ROS and oxidative bursts.
Thus, recent research has identified abiotic stress induced ROS
accumulation under control of MPK6, MKK1, and MKKK20 supporting a dynamic control of the signaling component ROS by
MPK6 and other components of the MAPK pathway (Xing et al.,
2008; Kim et al., 2012).
Novel findings uncover links of the MAPK cascade to cellular lipid transfer processes indicating a coupling of MAP-type
kinases to stress adaptive changes of membranes, intracellular membrane trafficking or probably to stress-dependent lipid
signaling. Thus, recent research advances proved direct regulation of MPK6 mediated phosphorylation of the plasma
membrane Na+ /H+ antiporter SOS1 by NaCl and by PA supporting relationships of lipids to MAPK signaling in plant salt
stress responses (Yu et al., 2010). Integration of MPK6 in differential signaling pathways has been additionally reported by
interaction of MPK6 with the Arabidopsis C2H2-type zinc finger protein ZAT6 that functions both in plant developmental
processes and in osmotic stress responses (Liu et al., 2013b).
In several recent studies, emphasis has been placed on detailed
characterization of co-regulation and interaction of the MAP
kinase pathway and ROS signaling within the cellular signaling framework thus further strengthening the understanding of
MAP kinase as a hub in signaling under environmental adversity. In rice, the salt responsive MAPK cascade is linked to
ROS signaling by the transcription factor SERF1 (salt-responsive

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Golldack et al.

ERF1; Schmidt et al., 2013b). Cotton MAPK GhMPK16 is
functionally involved in pathogen resistance, drought tolerance
and ROS accumulation indicating a role of GhMPK16 as an
interface between biotic and abiotic stress signaling (Shi et al.,
2011).

ROS SIGNALING IN PLANTS UNDER DROUGHT AND SALT
STRESS
Current concepts emphasize a central function of cellular ROS
as a signaling interface in plant drought and salt adaptation hat
links stress signals to regulation of metabolism and the cellular
energy balance (Figure 1). Significantly, environmental adversity
such as drought and salinity impairs cellular ionic and osmotic
homeostasis but additionally compromises photosynthesis, cellular energy depletion, and redox imbalances (e.g., Baena-González
et al., 2007; Abogadallah, 2010; Jaspers and Kangasjärvi, 2010;
Miller et al., 2010; Zhu et al., 2010). Excess generation and accumulation of ROS such as superoxide, hydrogen peroxide and nitric
oxide cause oxidative damages in the apoplastic compartment and
damages of cellular membranes by lipid peroxidation and have
an extensive impact on ion homeostasis by interfering ion fluxes
(Baier et al., 2005). Excess ROS amounts are particularly scavenged by antioxidant metabolites such as ascorbate, glutathione,
tocopherols and by ROS detoxifying enzymes as superoxide dismutase, ascorbate peroxidase, and catalase (Mittler, 2002; Neill
et al., 2002). Current models emphasize a dual regulatory function of ROS as a signaling molecule in plant drought and osmotic
stress tolerance by sensing the cellular redox state and in retrograde
signaling. Studies on transcription factors of the WRKY and basichelix-loop helix types enhanced the understanding of crosstalks
of osmotic and oxidative stress responsive signaling pathways significantly. Thus, Arabidopsis WRKY33 responds to osmotic and
oxidative stresses (Miller et al., 2008). Regulatory function of
bHLH92 and WRKY33 in ROS detoxification by targeting peroxidases and glutathione-S-transferases suggested a function of
the transcription factors in linking ROS scavenging to osmotic
and oxidative stress induced signaling (Miller et al., 2008; Jiang
and Deyholos, 2009; Jiang et al., 2009). Recent research advances
linked the regulation of Arabidopsis salt and osmotic stress tolerance to ROS-responsive WRKY15 and mitochondrial retrograde
signaling (Vanderauwera et al., 2012). Another recent advance in
understanding the importance of ROS in plant salt responses
was the discovery of a coupled function of plastid heme oxygenases and ROS production in salt acclimation (Xie et al., 2011).
These findings strongly suggest involvement of the chloroplast
to nucleus signaling pathway in plant salt adaptation (Xie et al.,
2011). Additionally, work on cross-species expression of a SUMO
conjugating enzyme has provided considerable insight into the
links of ROS, ABA dependent signaling and the sumoylation pathway in plant salt and drought tolerance (Karan and Subudhi,
2012). Functional relation of the maize bZIP transcription factor
ABP9, glutamate carboxypeptidase AMP1, and the ankyrin-repeat
protein ITN1 to ABA signaling, ROS generation and ROS scavenging further support interaction and correlation of ABA and
ROS related pathways as signaling nodes in plant adaptation to
drought and salt (Sakamoto et al., 2008; Zhang et al., 2011; Shi
et al., 2013).

Frontiers in Plant Science | Plant Genetics and Genomics

Drought, salt and signaling

THE SPECIFIC FUNCTION OF STOMATAL SIGNALING IN
PLANT DROUGHT AND SALT TOLERANCE
Constant dynamic regulation of stomatal aperture is obligatory for
successful adaptation of plants to abiotic stresses. Prevention of
excess water loss via transpiration depends on reliable adjustment
of stomatal closure to environmental adversity. Hence, elucidation of sensing and signaling in stomatal guard cells has been
attracting particular attention to understand regulation of stomatal conductance under conditions of drought and salinity. As
another example, in maize mutants of the E3 ubiquitin ligase
ZmRFP1, enhanced drought tolerance and decreased ROS accumulation indicated linked regulation of stomatal closure and ROS
scavenging (Liu et al., 2013a). The Arabidopsis plasma membrane
receptor kinase, GHR1 (GUARD CELL HYDROGEN PEROXIDERESISTANT1) linked ABA and H2 O2 signaling in stomatal closure
(Hua et al., 2012). In addition, GHR1 regulated an S-type anion
channel suggesting a node function of this receptor kinase in
ion homeostasis, ABA and H2 O2 mediated signaling pathways in
guard cells (Hua et al., 2012).
As aforementioned, the SnRK2 protein kinase OST1 (SnRK2
OPEN STOMATA 1) is a central regulator of stomatal aperture
and links guard cell movement to the ABA signaling network
(Sirichandra et al., 2009). OST1 targets NADPH oxidases, inward
K+ channels, Ca2+ -permeable channels and the slow anion
channel SLAC1 in stomatal guard cells (Sirichandra et al., 2009;
Vlad et al., 2009; Acharya et al., 2013). In addition, the SnRK2
protein kinase OST1 also targets voltage-dependent quickly activating anion channels of the R-/QUAC-type in guard cells (Imes
et al., 2013). These data suggest coordinated control of SLAC1mediated transport of chloride and nitrate and QUAC1-mediated
transport of malate in the same ABA signaling pathway (Imes
et al., 2013). Recently, the finding of direct dephosphorylation of SLAC1 by the PP2C (protein phosphatase 2C) ABI1
provided interesting evidence for a specific alternative regulatory mechanism of the anion channel SLAC1 (Brandt et al.,
2012).
Recent research uncovered co-regulation of ABA-induced
stomatal closure, guard cell H+ -ATPase and Mg-chelatase H subunit (CHLH; Tsuzuki et al., 2013). CHLH/ABAR is involved in the
chlorophyll biosynthetic process and a function of CHLH/ABAR
as a chloroplastic ABA receptor via plastid-to-nucleus retrograde ABA signaling has been suggested (Shen et al., 2006; Shang
et al., 2010; Du et al., 2012). In Arabidopsis, functional mutation of CHLH affected phosphorylation of H+ -ATPase and
blue light dependent stomatal regulation (Tsuzuki et al., 2013).
These findings validate importance of CHLH in linking the
ABA signaling network to the regulation of ionic homeostasis and blue light responses in guard cells and plant drought
tolerance (Tsuzuki et al., 2013). Interestingly, ABA-dependent
regulation of stomatal closure responds to mutation of the
phosphate transporter PHO1 and the vacuolar H+ -ATPase subunit A (Zimmerli et al., 2012; Zhang et al., 2013). Again, these
results support interaction and co-regulation of ion homeostasis
in guard cells via ion transport, ABA signaling, and regulation of stomatal aperture (Zimmerli et al., 2012; Zhang et al.,
2013). Intriguingly, the transporter ZIFL1 (Induced FacilitatorLike 1) mediates potassium fluxes and has a dual function in

April 2014 | Volume 5 | Article 151 | 20

Golldack et al.

regulating both cellular auxin transport and stomatal closure
(Remy et al., 2013).
In conclusion, recent research advances have elucidated a
molecular cellular signaling network for the understanding how
plants control and regulate adaptation to the abiotic stresses
drought and salinity. Essentially, molecular signaling components
in plant adaptation to environmental adversity have been connected to hub transcription factors, MAPK pathways, ROS and
lipid-derived pathways. Importantly, it is expected that further
and perspective advances in the network modeling of cellular abiotic stress signaling will provide new and efficient strategies for
improving environmental tolerance in crops.

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Drought, salt and signaling

Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Received: 16 January 2014; accepted: 01 April 2014; published online: 22 April 2014.
Citation: Golldack D, Li C, Mohan H and Probst N (2014) Tolerance to drought and
salt stress in plants: unraveling the signaling networks. Front. Plant Sci. 5:151. doi:
10.3389/fpls.2014.00151
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Golldack, Li, Mohan and Probst. This is an open-access article
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April 2014 | Volume 5 | Article 151 | 24

REVIEW ARTICLE
published: 16 May 2014
doi: 10.3389/fpls.2014.00170

The transcriptional regulatory network in the drought
response and its crosstalk in abiotic stress responses
including drought, cold, and heat
Kazuo Nakashima1 , Kazuko Yamaguchi-Shinozaki 2 and Kazuo Shinozaki 3 *
1

Biological Resources and Post-harvest Division, Japan International Research Center for Agricultural Sciences, Tsukuba, Japan
Laboratory of Plant Molecular Physiology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Tokyo, Japan
3
Gene Discovery Research Group, RIKEN Center for Sustainable Resource Science, Yokohama, Japan
2

Edited by:
Mukesh Jain, National Institute of
Plant Genome Research, India
Reviewed by:
Alejandra A. Covarrubias, Universidad
Nacional Autónoma de México,
Mexico
Kemal Kazan, Commonwealth
Scientific and Industrial Research
Organization, Australia
Eiji Nambara, University of Toronto,
Canada
*Correspondence:
Kazuo Shinozaki, Gene Discovery
Research Group, RIKEN Center for
Sustainable Resource Science, 1-7-22
Suehiro, Tsurumi, Yokohama,
Kanagawa 230-0045, Japan
e-mail: kazuo.shinozaki@riken.jp

Drought negatively impacts plant growth and the productivity of crops around the world.
Understanding the molecular mechanisms in the drought response is important for
improvement of drought tolerance using molecular techniques. In plants, abscisic acid
(ABA) is accumulated under osmotic stress conditions caused by drought, and has a key
role in stress responses and tolerance. Comprehensive molecular analyses have shown
that ABA regulates the expression of many genes under osmotic stress conditions, and
the ABA-responsive element (ABRE) is the major cis-element for ABA-responsive gene
expression. Transcription factors (TFs) are master regulators of gene expression. ABREbinding protein and ABRE-binding factor TFs control gene expression in an ABA-dependent
manner. SNF1-related protein kinases 2, group A 2C-type protein phosphatases, and ABA
receptors were shown to control the ABA signaling pathway. ABA-independent signaling
pathways such as dehydration-responsive element-binding protein TFs and NAC TFs are
also involved in stress responses including drought, heat, and cold. Recent studies have
suggested that there are interactions between the major ABA signaling pathway and
other signaling factors in stress responses. The important roles of these TFs in crosstalk
among abiotic stress responses will be discussed. Control of ABA or stress signaling factor
expression can improve tolerance to environmental stresses. Recent studies using crops
have shown that stress-specific overexpression of TFs improves drought tolerance and
grain yield compared with controls in the field.
Keywords: ABA, transcription factor, signal transduction, abiotic stress, drought

INTRODUCTION
The world population is expected to reach nine billion by
2050. Considering this population increase, crop yields need
to be improved by 40% in areas where drought is likely to
occur by 2025 (Pennisi, 2008). In addition, frequent occurrences of drought and abnormal weather events have lately been
observed all over the world. Drought negatively impacts plant
growth and crop production (Bray et al., 2000). Almost every
year, some region of the earth is hit by drought, damaging
crops, and disrupting agricultural production. Severe drought
affected the central and south of the US Corn Belt during
2012 (Edmeades, 2013). Drought also causes great damage to
the production of other crops such as rice, wheat, and soybean. The southern states of Brazil, which account for 40%
Abbreviations: ABA, abscisic acid; ABF, ABRE-binding factor; ABRE, ABAresponsive element; AP2, APETALA 2; AREB, ABRE-binding protein; bZIP, basic
leucine zipper; CBF, CRT binding factor; CE, coupling element; DRE, dehydrationresponsive element; DREB, DRE-binding protein; DRIP, DREB2A-interacting
protein; CRT, C-repeat; ERF, ethylene-responsive element binding factor; GWAS,
genome-wide association study; NAC, NAM, ATAF, and CUC; PP2C, 2C-type protein phosphatase; PYL, PYR1-like; PYR, pyrabactin resistance; QTL, quantitative
trait locus; RCAR, regulatory component of ABA receptor; SNAC, stress-responsive
NAC; SnRK2, SNF1-related protein kinase 2; TF, transcription factor.

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of the soybean production by the second leading producer
worldwide, lost more than 20% of their production because of
drought during the 2003/2004 and 2004/2005 seasons (Polizel
et al., 2011). The development of stress-tolerant crops will be
significantly advantageous in areas where such stresses occur
frequently. Recently, some progress has been made toward identification of stress-related genes potentially capable of increasing the tolerance of plants to abiotic stress. Understanding
the molecular mechanisms in the drought response is important to improve drought tolerance using molecular techniques.
ABA accumulates under osmotic stress caused by drought, but
also by other water limiting conditions, and plays an important role in stress responses and tolerance in plants (reviewed
in Finkelstein et al., 2002; Yamaguchi-Shinozaki and Shinozaki,
2006; Nakashima et al., 2009b; Figure 1). Molecular studies have
revealed that ABA-independent gene expression is also important in stress tolerance in plants (Figure 1). In this review,
we summarize some of the most important TFs in drought
responses and discuss their regulatory networks and crosstalk in
abiotic stress responses. By applying current knowledge of stressregulated TFs and their target genes, improvement of drought
stress tolerance is in progress in various crops using transgenic
technology.

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Transcriptional regulation in drought responses

et al., 2013). Progress in understanding ABA perception and signal transduction has been made recently (reviewed in Cutler et al.,
2010; Raghavendra et al., 2010; Umezawa et al., 2010; Weiner et al.,
2010; Nakashima and Yamaguchi-Shinozaki, 2013). It was revealed
that SnRK2, group A PP2Cs, and RCAR/PYR/PYL ABA receptors
control the ABA signaling pathway including AREB/ABFs in land
plants (reviewed in Umezawa et al., 2010; Miyakawa et al., 2013;
Nakashima and Yamaguchi-Shinozaki, 2013). The phosphorylation of AREB/ABFs by SnRK2s is critical in the ABA-dependent
signaling network (Fujita et al., 2009; Nakashima et al., 2009a;
Umezawa et al., 2013). Recent studies have indicated that group
A PP2Cs evolved early in land plants as key regulators of intrinsic
desiccation tolerance, such as in the moss Physcomitrella patens
(Komatsu et al., 2013). Perception and signaling factors such as
PYL4 can also be used to improve stress tolerance (Pizzio et al.,
2013).

FIGURE 1 | Utilization of transcription factors (TFs) involved in
stress-responsive pathways in stress responses for the improvement
of drought tolerance of crops. Usage of suitable promoters might be
necessary to control their expression.

AREB/ABF TFs FOR ABA-DEPENDENT GENE EXPRESSION
The promoter regions of ABA-responsive genes contain a conserved cis-element, named the ABRE (PyACGTGG/TC), which
controls gene expression (Figure 1). Studies have revealed that
expression of ABA-responsive genes requires more than one ABRE
or a combination of an ABRE and a CE for a functional promoter (reviewed in Fujita et al., 2011, 2013; Nakashima and
Yamaguchi-Shinozaki, 2013). Comprehensive and molecular analyses showed that ABA regulates the expression of many genes
under osmotic stress conditions, and that the ABRE is the major
cis-element for ABA-responsive gene expression (Maruyama et al.,
2012). AREB/ABFs are bZIP TFs that regulate ABA-dependent
gene expression, acting as major TFs under abiotic stress conditions in Arabidopsis (reviewed in Fujita et al., 2011, 2013; Figure 1).
Among the nine members of the AREB/ABF TF family identified
in Arabidopsis, AREB1/ABF2 has been reported to control ABA
signaling and environmental stress responses during the vegetative growth stage. The AREB/ABF TFs are induced by abiotic
stress and their transcriptional activities are controlled by ABAdependent phosphorylation. ABA is required for full activation
of AREB1 (Fujita et al., 2005; Yoshida et al., 2010) and its activity
is regulated by the ABA-dependent phosphorylation of multiple
sites within conserved domains (Furihata et al., 2006). Transgenic
Arabidopsis plants overexpressing deleted and active forms of
AREB1 showed enhanced drought tolerance and ABA hypersensitivity (Fujita et al., 2005). Overexpression of AREB1 also improved
drought tolerance in rice and soybean (Oh et al., 2005; Barbosa

Frontiers in Plant Science | Plant Genetics and Genomics

DREB1/CBF TFs FOR COLD-RESPONSIVE GENE EXPRESSION
TO IMPROVE DROUGHT TOLERANCE
Analysis of the promoter regions of genes showing ABAindependent expression in stress responses and tolerance has
shown a cis-element with the sequence A/GCCGAC, designated
the DRE/CRT (Figure 1). Two groups of AP2/ERF TFs were identified as DREB; DREB1/CBF and DREB2 in Arabidopsis (Liu et al.,
1998). DREB1/CBF TFs specifically interact with the DRE/CRT
and control the expression of a large number of stress-responsive
genes in Arabidopsis. Improvements in tolerance to drought,
salinity and freezing stresses have been reported in transgenic
Arabidopsis overexpressing DREB1/CBF TFs, although their constitutive expression causes growth defects (Liu et al., 1998; Kasuga
et al., 1999). However, overexpression of DREB1 under the control
of the Arabidopsis stress-responsive RD29A promoter improved
stress tolerance in Arabidopsis without growth defects (Kasuga
et al., 1999). Cold-inducible DREB1/CBF genes have also been
isolated from a number of plant species, such as maize, oilseed
rape, rye (Secale cereale), rice, tomato, and wheat (Triticum aestivum; reviewed in Mizoi et al., 2012). Interestingly, the major
QTLs for tolerance to frost in Arabidopsis, diploid wheat (T.
monococcum) and barley map to DREB1/CBF genes, and the
expression levels of DREB1/CBF genes are correlated with frost
tolerance (Vágújfalvi et al., 2003; Alonso-Blanco et al., 2005; Francia et al., 2007; Knox et al., 2008). Thus, the function of the
DREB1/CBF regulon in the regulation of cold stress responses is
widely conserved in angiosperms. Overexpression of DREB/CBF
TFs has been reported to enhance drought tolerance in transgenic crops including chrysanthemum (Hong et al., 2006), peanut
(Bhatnagar-Mathur et al., 2007, Bhatnagar-Mathur et al., 2013),
potato (Behnam et al., 2007; Iwaki et al., 2013), rice (Oh et al.,
2005; Ito et al., 2006; Datta et al., 2012), soybean (Polizel et al.,
2011; de Paiva Rolla et al., 2013), tobacco (Kasuga et al., 2004),
tomato (Hsieh et al., 2002a,b), and wheat (Pellegrineschi et al.,
2004; Saint Pierre et al., 2012). For example, rice DREB1/CBF-type
TFs involved in cold-responsive gene expression also conferred
improved tolerance to drought in transgenic rice (Ito et al., 2006).
The rice DREB1/CBF-type genes, OsDREB1A and OsDREB1B, are
induced by cold stress. Transgenic Arabidopsis and rice plants overexpressing rice OsDREB1 or Arabidopsis DREB1 genes showed

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Nakashima et al.

improved tolerance to drought, high-salt and cold stresses but
defective growth under normal growth conditions. Elevated contents of osmoprotectants including free proline and soluble sugars
were detected in the transgenic rice. These results indicate that the
DREB1/CBF regulon is conserved in rice, and that DREB1/CBFtype genes may be useful for improvement of tolerance to different
environmental stresses in various kinds of transgenic monocot
plants as well as dicot plants.

DREB2 TFs FOR OSMOTIC- AND HEAT-RESPONSIVE GENE
EXPRESSION TO IMPROVE DROUGHT TOLERANCE
The DREB2 gene encoding a DRE/CRT-binding protein is induced
by osmotic stress (Liu et al., 1998; Figure 1). However, transgenic plants overexpressing DREB2A did not show any changes
in phenotype. Domain analysis of DREB2A using Arabidopsis
protoplasts showed that deletion of the central region makes
DREB2A constitutively active (DREB2Aca), indicating that this
region contains a negative regulatory domain (NRD; Sakuma et al.,
2006a). Overexpression of DREB2Aca induced growth defects,
up-regulation of stress-inducible genes, and enhanced drought
tolerance (Sakuma et al., 2006a). Stress-inducible overexpression
of DREB2ca improved drought tolerance in Arabidopsis and soybean without growth defects (Sakuma et al., 2006a; Engels et al.,
2013). The NRD region of DREB2A is required for regulation of
DREB2A protein stability. As mentioned above, overexpression
of DREB1A improves freezing and dehydration stress tolerance
in transgenic plants. By contrast, overexpression of DREB2Aca
improves dehydration stress tolerance but only slightly improves
freezing stress tolerance in transgenic plants. Integrated analysis
of transcripts and metabolites was conducted to see the difference in the downstream gene products of DREB1A and DREB2A
in Arabidopsis (Maruyama et al., 2009). Microarray analysis indicated that the downstream gene products of DREB1A and those
of DREB2A have similar putative functions, but the expression
of genes for carbohydrate metabolism in DREB1A and DREB2A
transgenic plants is very different. Under dehydration and cold
conditions, expression of genes for starch-degradation, sucrose
metabolism and sugar alcohol synthesis changes dynamically. As
a result, many kinds of mono-, di-, and trisaccharides, and
sugar alcohols accumulate in plants. Overexpression of DREB1A
caused similar changes in these metabolic processes, and these
changes might improve dehydration and freezing stress tolerance
in transgenic plants. By contrast, overexpression of DREB2Aca
did not increase the level of these metabolites in transgenic
plants. In addition, degradation of DREB2A is mediated by
DRIPs, which are C3HC4 RING domain-containing proteins.
DRIPs bind to DREB2A and function as E3 ubiquitin ligases
mediating ubiquitination of DREB2A (Qin et al., 2008). Overexpression of DREB2Aca also induced expression of genes related
to heat shock stress and improved thermotolerance in transgenic plants (Sakuma et al., 2006b). These results indicate that
DREB2s function in both dehydration and heat shock stress
responses. DREB2-type proteins have been isolated from a number of other plant species such as barley, rice, sunflower, maize,
and wheat (Mizoi et al., 2012). GmDREB2A;2 is a DREB2A
ortholog in soybean (Mizoi et al., 2013), but there are differences between DREB2A and GmDREB2A;2 in the NRD sequence.

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Transcriptional regulation in drought responses

The effects on gene expression in transgenic plants overexpressing
GmDREB2A;2 are different from those in transgenic plants overexpressing DREB2A. This suggests that specialization in DREB2
regulons has occurred, although their basic functions are conserved between Arabidopsis and soybean. Recently, GWAS of
ZmDREB2 and natural variations in the drought tolerance of
maize (Zea mays) indicated that natural variation in the promoter
region of ZmDREB2.7 contributes to drought tolerance in maize
(Liu et al., 2013). The favorable ZmDREB2.7 allele may be a good
resource for improving drought tolerance in maize. Recent studies
suggest that DREB2 has important functions in drought tolerance,
and that it can be used for improvement of drought tolerance in
crops.

NAC TFs FOR DROUGHT-RESPONSIVE GENE EXPRESSION TO
IMPROVE DROUGHT TOLERANCE
NAM, ATAF, and CUC TF proteins are plant-specific TFs. More
than 100 NAC genes have been identified in Arabidopsis and rice
(reviewed in Nakashima et al., 2012). Phylogenetic analyses indicate that six groups were established in an ancient moss. NAC
TFs have a variety of important functions in development and
stress responses. The genes in the SNAC group have important
roles in the control of environmental stress tolerance (reviewed in
Nakashima et al., 2012; Figure 1), and can bind to the NACR (NAC
recognition sequence; CACG core). Stress-responsive Arabidopsis
SNAC genes such as RD26 and ATAF1, and rice SNAC genes such
as SNAC1, OsNAC6/SNAC2, and OsNAC5 can improve drought
and/or high-salt stress tolerance when overexpressed (Tran et al.,
2004; Hu et al., 2006; Nakashima et al., 2007; Takasaki et al., 2010;
reviewed in Nakashima et al., 2012). Stress-responsive overexpression of NACs utilizing rice stress-responsive LIP9, OsNAC6, or
OsHox24 promoters is effective in inducing stress tolerance without the inhibitory effects of NAC on plant growth (Nakashima
et al., 2007, 2012, 2014; Takasaki et al., 2010). Recent studies have
suggested that the root-specific promoter RCc3 is useful for the
overexpression of SNACs such as SNAC1 and OsNAC10 to enhance
the abiotic stress tolerance of rice in field conditions (Jeong et al.,
2010, 2013; Redillas et al., 2012). These results indicate that SNACs
have important roles in the control of abiotic stress responses and
tolerance and that it is possible to improve stress tolerance by overexpressing SNACs using suitable promoters in the field. The many
kinds of drought-responsive or tissue/organ-specific promoters
reported for roots and stomata might be effective tools to control
the expression of drought-responsive factors that cause growth
defects at the right time and right position (Nakashima et al., 2007,
2014; Rai et al., 2009; Wu et al., 2009; Xiao et al., 2009; Yi et al.,
2010; Ganguly et al., 2011; Yang and Xiong, 2011; Bang et al., 2013;
Rusconi et al., 2013).
INTERACTIONS BETWEEN MULTIPLE TFs IN DROUGHT
RESPONSES
Evidence for interaction between the AREB/ABFs and DREB/CBFs
has been reported. The DRE/CRT motif in the promoters of drought-responsive genes is a binding region for an
ABA-independent DREB/CBF TF and functions as a CE for
ABRE in ABA-dependent gene expression (Narusaka et al., 2003).
Lee et al. (2010) showed that the DREB1A/CBF3, DREB2A,

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Nakashima et al.

and DREB2C proteins interact physically with AREB/ABF proteins. These data suggest crosstalk between elements of the
ABA-dependent and -independent response pathways. Moreover,
interactions in the signaling pathways have also been indicated.
Kim et al. (2011) reported that an ABRE promoter sequence,
AREB/ABF TFs, and SnRK2s are involved in expression of the
DREB2A gene under osmotic stress conditions, suggesting complex interaction between the AREB and DREB regulons at the gene
expression level as well as the protein level.
Interaction between the AREB/ABFs and NACs has also been
indicated at the gene expression level. Jensen et al. (2013) reported
that Arabidopsis SNAC TF ATAF1 directly regulates the ABA
biosynthetic gene NCED3 in Arabidopsis, suggesting that SNAC
TFs may regulate ABA-dependent gene expression of ABRE
regulons. On the other hand, the promoters of SNAC genes
contain ABRE sequences (Nakashima et al., 2012). Recently, Xu
et al. (2013) reported that Arabidopsis ANAC096 cooperates with
AREB/ABF factors (ABF2/AREB1 and ABF4/AREB2) in dehydration and osmotic stress responses. These results indicate complex
interaction between the AREB/ABF and NAC regulons.
Finally, interaction between DREB/CBFs and other kinds of
AP2/ERFs at the gene expression level has also been suggested.
Cheng et al. (2013) reported that the Arabidopsis ERF1 regulates
gene expression by binding to two kinds of cis-elements, the GCC
box and DRE/CRT, in response to different stress signals. ERF1 is
an upstream TF in both ethylene and jasmonate signaling and is
involved in resistance to pathogens. Their results suggested that
ERF1 bound to the GCC box but not the DRE/CRT in response
to biotic stress, and to the DRE/CRT under abiotic stress. These
results suggest that ERF1 may integrate ethylene, jasmonate, and
ABA signaling and play an important role in biotic and abiotic
stress responses.

CONCLUSION
Molecular analysis has suggested that drought-responsive TFs such
as DREB1/CBF, DREB2, AREB/ABF, and NAC TFs function in
drought responses and tolerance (Figure 1). These TFs also function in crosstalk in abiotic stress responses, such as drought,
cold, and heat. As mentioned above, these factors can be used
to improve drought tolerance in a variety of crops. Our group
has utilized these key TFs for the improvement of drought tolerance in crops including rice, wheat, and soybean in collaboration
with international and domestic institutes (Pellegrineschi et al.,
2004; Hong et al., 2006; Behnam et al., 2007; Bhatnagar-Mathur
et al., 2007; Polizel et al., 2011; Datta et al., 2012; Ishizaki et al.,
2012; Saint Pierre et al., 2012; Barbosa et al., 2013; BhatnagarMathur et al., 2013; de Paiva Rolla et al., 2013; Engels et al.,
2013; Iwaki et al., 2013). Some results using crops including
rice and peanut have shown that stress-specific overexpression of
DREB1A improves drought tolerance and grain yield compared
with controls in the field (Datta et al., 2012; Bhatnagar-Mathur
et al., 2013). These results suggest that overexpression of key TFs
under the control of suitable promoters can improve stress tolerance, although the regulatory network in the plant response is
complex in water limiting environments (Figure 1). Since TFs
function in balanced crosstalk in abiotic stress responses, overexpression of a certain TF may affect other signaling pathways.

Frontiers in Plant Science | Plant Genetics and Genomics

Transcriptional regulation in drought responses

Thus, we should examine the molecular effects of overexpressing TFs in addition to conducting stress tolerance assays. In
addition, the effects of a transgene may depend on the genetic
background of the species or cultivar used for transformation.
Furthermore, since the degree of drought varies in actual fields
(strength, timing, and period of stress, complex stresses such as
drought with heat stress etc.), the effect of a transgene may differ
depending on environmental conditions. Continuous field experiments might be necessary to see the effects of transgene-encoded
TFs in the field using a variety of genotypes and environments.
Recently, QTL analyses have revealed novel genes involved in
drought resistance. DEEPER ROOTING 1 (DRO1), a QTL controlling root growth angle in rice, was cloned and characterized
(Uga et al., 2013). This study revealed that changes in root system architecture can improve drought avoidance. Other drought
resistant QTLs have also been reported in rice. Multiple QTLs
were reported in the rice mega-variety IR64 that enhance the
yield under drought conditions (Swamy et al., 2013). Combinations/pyramiding of transgenic plants and QTL drought resistant
varieties by marker-assist selection (MAS) may promote drought
tolerance.

ACKNOWLEDGMENTS
We thank Masami Toyoshima for skillful editorial assistance.
Research in our laboratories was supported by the Program for
Promotion of Basic and Applied Researches for Innovations in Biooriented Industry (BRAIN); the Ministry of Agriculture, Forestry
and Fisheries (MAFF); the Science and Technology Research Partnership for Sustainable Development (SATREPS) of the Japan
Science and Technology Agency (JST)/Japan International Cooperation Agency (JICA); Grants-in-Aid for Scientific Research by
the Ministry of Education, Culture, Sports, Science and Technology (MEXT) and the Japan Society for the Promotion of Science
(JSPS).

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Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.

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Transcriptional regulation in drought responses

Received: 04 February 2014; accepted: 10 April 2014; published online: 16 May
2014.
Citation: Nakashima K, Yamaguchi-Shinozaki K and Shinozaki K (2014) The transcriptional regulatory network in the drought response and its crosstalk in abiotic stress
responses including drought, cold, and heat. Front. Plant Sci. 5:170. doi: 10.3389/fpls.
2014.00170
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Nakashima, Yamaguchi-Shinozaki and Shinozaki. This is an
open-access article distributed under the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original
publication in this journal is cited, in accordance with accepted academic practice.
No use, distribution or reproduction is permitted which does not comply with these
terms.

May 2014 | Volume 5 | Article 170 | 31

REVIEW ARTICLE
published: 28 May 2014
doi: 10.3389/fpls.2014.00224

Physiological and genomic basis of mechanical-functional
trade-off in plant vasculature
Sonali Sengupta * and Arun Lahiri Majumder
Division of Plant Biology, Acharya J C Bose Biotechnology Innovation Centre, Bose Institute, Kolkata, India

Edited by:
Mukesh Jain, National Institute of
Plant Genome Research, India
Reviewed by:
Adriana Garay, Universidad Nacional
Autónoma de México, Mexico
Li Yang, University of North Carolina
Chapel Hill, USA
*Correspondence:
Sonali Sengupta, Division of Plant
Biology, Acharya J C Bose
Biotechnology Innovation Centre,
Bose Institute, P-1/12, C.I.T. Scheme
VIIM, Kolkata 700 054, India
e-mail: sonalisengupta2000@
yahoo.co.in

Some areas in plant abiotic stress research are not frequently addressed by genomic
and molecular tools. One such area is the cross reaction of gravitational force with
upward capillary pull of water and the mechanical-functional trade-off in plant vasculature.
Although frost, drought and flooding stress greatly impact these physiological processes
and consequently plant performance, the genomic and molecular basis of such trade-off
is only sporadically addressed and so is its adaptive value. Embolism resistance is an
important multiple stress- opposition trait and do offer scopes for critical insight to unravel
and modify the input of living cells in the process and their biotechnological intervention
may be of great importance. Vascular plants employ different physiological strategies to
cope with embolism and variation is observed across the kingdom. The genomic resources
in this area have started to emerge and open up possibilities of synthesis, validation and
utilization of the new knowledge-base. This review article assesses the research till date
on this issue and discusses new possibilities for bridging physiology and genomics of a
plant, and foresees its implementation in crop science.
Keywords: embolism, cavitation, xylem, drought, freezing, mechanical stress

INTRODUCTION
A green plant is unique in its hydraulic architecture. Hydraulic
conductivity of the xylem is closely linked to the minimum leaf
area, which it must supply with water and nutrients for survival.
Hydraulic conductivity, as quantified by Zimmermann (1974), is
generally measured as leaf specific conductivity (flow rate per unit
pressure gradient) divided by the leaf area supplied by the xylem
pipeline segment. This measure is a key for quick evaluation of
pressure gradients within a plant. Modeling the functional and
natural architecture of plant water flow pipeline takes more traits
in consideration than merely the physical attributes of a mechanical pump. The contribution of living cells and more specifically,
genes and proteins, for maintenance of the “green pump” remains
largely unaddressed.
Several theories have been proposed to explain ascent of sap.
The operation of the green pump is simple yet elegant and is
best described by the Cohesion-Tension Theory (CTT) (Dixon,
1914) but also synthesized from the work of many scientists over
the last few decades. Besides physical explanations, the living
parenchyma cells around xylem were originally proposed to be
of importance by Bose (1923) in his pulsation theory. Later, the
living xylem parenchyma cells indeed proved of high importance
for the continuous ascent of sap.
The major governing factors are the physical properties of
aqueous solution, means of transport and xylem anatomy, consideration of all of which makes the “sap conducting system”
comparable to basic hydraulic systems such as pumps and irrigations in household or human blood vasculature. Components of
such system are mainly (i) a driving force, (ii) a pipeline system,
(iii) a reservoir and other regulating factors. To establish a soilwater-atmosphere continuum, an uninterrupted “water network”

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is necessary, which is built in the plant where transpirational
evaporation is the driving force (Figure 1A). The evaporation of
water from the porous green tissue surface creates a capillary pull
in the water menisci (Figure 1Ai) and a curvature is induced in
them, which is sufficient to support a huge water column against
gravity in the stem and root vascular cylinder (Figure 1Aii). The
water reservoir is the soil, wherefrom the root draws its supply
(Figure 1Aiii). The empirical Jurin law says that a menisci radius
of 0.12 µm can support a column of 120 m (Zimmermann, 1983).
The pull creates sub-atmospheric pressure in the xylem vessels.
As the height of a plant increases, the water potential drops, and
it is expected that leaves, twigs and upper extremities will display
a 10–1000 times drop of pressure (Figure 1A, Tyree and Sperry,
1989). Sixty five percentage of the water potential drop occurs in
tree trunk xylem, with a 20% contribution from root and 14%
from leaves (Tyree and Sperry, 1989). This explains why big tree
trunks can survive severe localized damages near the base.

PLANT ARCHITECTURE AND THE GREEN PUMP
Architecture of a plant is defined by its height, girth, woodiness,
root system design and shoot disposition. Such architecture varies
across the plant kingdom, along which varies the plants’ hydraulic
nature. Secondary thickening is a major player that governs the
green pump. It has been shown that root pressure plays little or
no part in maintenance of this column in woody plants. Severing
the root may not hamper upward movement of water, if there is
a direct supply to the vessels; however leaves are necessary. Even
the best vacuum pump is able to pull water to not more than
10.4 m, considering that a Sequoia tree may have to pull water up
to 100 m. However, in the monocots, root pressure is considered
to be a major player of sap pull.

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FIGURE 1 | (A) The soil-plant-air continuum functioning in maintenance of
water transport column. The plant root takes up water from soil, and the
water column is maintained continuous along the xylem. The continuity
across the xylem vessel is maintained by several intrinsic physical properties
of water, input from the adjoining living cells and transpirational pool. The
rough estimate of pressure along the vascular cylinder is presented in the
scale bar (image not to actual scale). (B) A schematic of xylogenesis, adapted
and modified from Hertzberg et al., 2001. The two phases of xylem

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Genomics of plant vasculature

development (primary and secondary); and the tissues involved in the
process are shown within respective dotted boxes. The biological processes
(cell division, expansion, elongation, deposition of cell wall) involved are
shown by black arrows, under corresponding tissue types. The cell wall
materials that are deposited are also shown under corresponding tissue
types during xylogenesis. The order of such differentiation may be traced
from left to right in the figure, though their actual time frame may differ from
species to species.

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Sengupta and Majumder

Considering the physical properties of green-pump, cavitation
and embolism are major threats to the water column in xylem
and subsequently, to survival, across the kingdom. To successfully
transport water and minerals from soil to leaf, existing pressure
in xylem conduits needs to remain sub-atmospheric (negative), in
contrast to animal system where long distance transport is actively
under positive pressure. The molecular property of cohesion gives
a high strength to water. Ultrapure water confined to tubes of very
small bore will need a tension comparable to the strength needed
to break steel columns of the same diameter. Cohesion imparts
strength comparable to solid wires in a water column. The vice is:
once air is introduced in such system, the column will snap apart.
To prevent such snapping, xylem properties play an important
role.

PHYSIOLOGY OF XYLOGENESIS: THE BIPHASIC
DEVELOPMENT IN XYLEM
The biphasic development of xylem in plants is critical to understand the hydraulic architecture as well as the air-water-soil
continuum (Figure 1B). Procambium develops into xylem precursor cells that eventually differentiate into xylem fiber cells,
xylem parenchyma, and tracheary elements, consisting of vessels
and tracheids in the first phase. The second phase deposits secondary xylem walls onto the primary xylem walls (Fukuda, 1997;
De Boer and Volkov, 2003), derived from vascular cambium and
made of cellulose microfibrils impregnated with lignin, structural
proteins, hemicellulose and pectin (Figure 1B, Ye, 2002; Fukuda,
2004; Yokoyama and Nishitani, 2006). Prior to secondary development, the tracheary components elongate and with the advent
of secondary wall deposition, the cellular components in the living tracheid undergo programmed cell death (Fukuda, 2004)
living only the hollow pipeline (Fukuda, 1997; Zhang et al., 2011)
composed of vessels interconnected by pits (De Boer and Volkov,
2003; Choat and Pittermann, 2009). The paired pits are often
bordered (Figure 1A); from secondary deposition forming two
overarched secondary walls, in between which a fine pit membrane with small pores persist. Pit membranes are made up of
meshes of polysaccharide (Tyree and Zimmermann, 2002; PérezDonoso et al., 2010) and allow axial passage of water and small
molecules. Besides, they act as safety protection against spread of
air seeds (Tyree and Zimmermann, 2002; De Boer and Volkov,
2003; Choat et al., 2008; Pérez-Donoso et al., 2010).

PHYSIOLOGY OF CAVITATION
The negative pressure in the xylem may descend low enough to
make the water metastable. To achieve non-disrupted flow in such
system, water must remain liquid below its vapor pressure. This
metastable state induces nucleation of vaporization, or cavitation.
Cavitation is the introduction of air spaces into the continuous
water column and under physical metastable state water is prone
to form air bubbles easily. Introduced in a xylem lumen, air cavities rupture the water column and in its worst, block the transport
of water and minerals to the leaf. This blockage is known as
“embolism” and may lead the plant to a lethal fate.
Cavitation is known to occur in plants frequently.
Paradoxically, occurrence of cavitation is the strongest support for CTT. It is only natural to observe cavitation if water is

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Genomics of plant vasculature

under such negative pressure. The root vessels of field grown,
well watered maize plants have been known to embolize daily
and then refill. Vessels that were filled by dawn may embolize at
mid-afternoon and by sunset they are again refilled (McCully
et al., 1998). When transpiration rate is high and water scarcity
is at bay, trees display cavitation, which means that embolism
can well be induced by water stress. Large metaxylem vessels
show a higher rate of embolism, and evidence suggest that water
stress-induced embolism is of the frequent most sort (Tyree and
Sperry, 1989). It is a prerequisite for cavitation that some vessels
are embolized to start with; which is met by bubbles introduced
in some of the vessels by mechanical damage, harbivory and
insect attack.

STRESS-INDUCED EMBOLISM IN PLANTS
Both abiotic and biotic stresses can induce embolism in a plant.
Drought and frost—induced embolisms are most prevalent, while
mechanical stress and pathogen-induced damage are often the
primary inducers.
Desert plants and dry-season crops are most threatened
by drought-induced embolism. Air-seeding increases during
drought as the sap pressure becomes increasingly negative due
to high suction. The evaporation from leaf surface increases and
the porous conduit wall may release air inside the functional
conduits. They behave as nucleation centers and cause the sap
pressure to increase to atmospheric level. The bubble is then likely
to start an embolism that fills up the diameter of conduit, as the
surrounding water is pulled up by transpiration.
Interconduit pit membranes with nano-scale pores normally
restrict passage of air bubble from affected to functional conduits
but at a high pressure difference they fail to stop the propagation. The rate of this propagation is important to measure the
cavitation resistance in a plant.
Freezing is another cause of embolism, specially in woody temperate species. Freeze-thaw cycles may lead to 100% loss of water
transport due to embolism in some species (Scholander et al.,
1961). The primary governing factor in damage intensity seems
to be the mean diameter of the conduits. Smaller vessel diameters
are more vulnerable to damage.
Frost-induced air seeding is caused by segregation of gas by
ice. There is a certain amount of salting out from the sap during freezing of sap, and if the salts are not able to move through
the walls, they raise the osmotic pressure of remaining solution
(Sevanto et al., 2012). This embolism can be more severe if there
is functional drought prevailing. Freezing-induced embolism is a
primary stress in forests where seasonal freeze-thaw is observed.
Herbaceous plants, on the other hand, hardly survive freezing and
are mostly at threat from drought-induced embolism.
Vascular wilt pathogens can wipe out entire crop. It is known
that vascular pathogens induce water stress in their hosts; but can
embolism be a cause of such stress? All vascular wilt pathogens
break into rigid secondary xylem walls to enter the vessels as well
as the pit membranes. Generally vascular wilt pathogens or their
spores and conidia are too large to pass through pit membrane
pores (Mollenhauer and Hopkins, 1974; Choat et al., 2003, 2004;
Qin et al., 2008). Even when they manage to break into the vessel the milieu is not friendly. The microenvironment of xylem

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Sengupta and Majumder

pipeline is nutritionally very poor and the pathogens surviving in
xylem niche are not too many in number. It is speculated that they
prefer this environment to minimize competition. Nevertheless,
fungal and bacterial pathogens can extract the little amount of
ions and nutrients available in the xylem stream and are able to
break through and digest secondary wood to leech nutrition from
living cells. Doing so, they weaken the pressurized cell wall and
their infestation within the dead pipeline makes the water stream
reactive and prone to cavitation. They may as well block the vessels and pit membranes, occluding parts of functional conduit
network.
There is also an internal mechanical stress associated with
ascent of sap. The high negative tension within the xylem pipeline
causes an inward pool. Depending on the sapwood elasticity, there
is a daily diameter change of tree trunk correlated to transpiration and daylight. In Scots pine, Perämäki et al. (2001) described
daily changes in the sapwood diameter. The pull causes pressure
on a stem surface element directed toward the center of the stem
and the tracheal structure resists the movement of the surface
element. The mechanical strength of the tracheary wall and its
composition is, hence, an important factor in maintaining normal xylem activity as is the plasticity of pit membrane structure
and composition.

VULNERABILITY OF XYLEM TO CAVITATION
Xylem seems to be vulnerable to cavitation in many different
ways. This vulnerability can vary depending on the species, season, and availability, state and temperature of water. Broadly, the
vulnerability of plants to cavitation is often plotted on xylem
vulnerability curves, which is a function of decline in xylem
hydraulic conductivity due to increasingly negative xylem pressure. Such declines are typically expressed relative to the maximum decline possible as the Percentage Loss of Conductivity
(PLC). Comparisons of the vulnerability to cavitation among
species are made using the xylem pressure at 50% loss of conductivity (P50 ) with the traditional plotting of vulnerability
curve (Meinzer and McCulloh, 2013). There remain controversies
related to the techniques used for measurement of vulnerability
described elsewhere in details (McElrone et al., 2012; Cochard
et al., 2013; Wheeler et al., 2013).
The vulnerability curve for a number of tree species, as put
forward by Tyree et al. (1999) shows a typical exponential shape,
indicating that sub-zero pressure is a direct inducer of cavitation. This makes cavitation a regular process and necessitates a
resistance mechanism in plants. It has also been claimed that cavitation is rapidly repaired by a miraculous mechanism (Holbrook
and Zwieniecki, 1999) known as “refilling.” We can thus categorize cavitation resistance under two proposed mechanisms; one,
by refilling the air bubbles efficiently; and two, by modulating pit
membrane properties. The possible genetic controls of both are
worthy of discussion.

CAVITATION RESITANCE BY REFILLING: A QUESTIONABLE
TRAIT
The removal of air seeds from lumen to turn a non-functional
vessel to functional is known as refilling. The idea, though widely
observed, recently was confronted with a serious doubt voiced by

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Genomics of plant vasculature

the plant hydraulic scientists. The long-established experimental procedure that has been followed to measure cavitation has
been pronounced faulty (Sperry, 2013). It has been claimed that
the standard procedure of xylem hydraulic conductivity measurement, by excising the stem under water to avoid air aspiration in
the open conduits, is not a valid observation procedure. It has
been suggested that in many species, significant amount of cavitation is introduced even when the stem is cut under water. The
consequences of this artifact on previous datasets were significant, as it may be reflected in all vulnerability to cavitation curves
obtained in other species for a long period of time; and perturb
our analysis of refilled vessels.
However debatable the issue may be, recent high resolution
and real-time imaging studies (Holbrook et al., 2001; Windt et al.,
2006; Scheenen et al., 2007; Brodersen et al., 2010) also satisfy
the requirements of the hypothesis that plant has some kind
of resistance strategies to protect itself from embolism. It has
been proposed that plants have an osmotically driven embolism
repair mechanism and existing rehydration pathways through the
xylem. The mechanisms were predicted to be largely of two types:
(i) “novel” refilling, a refilling mechanism without “positive root
pressures, even when xylem pressures are still substantially negative”; (ii) root pressure aiding the refilling of vessels raising
the pressure inside vessels near atmospheric (Salleo et al., 1996;
Holbrook and Zwieniecki, 1999; Tyree et al., 1999; Hacke and
Sperry, 2003; Stiller et al., 2005). The first type is common among
woody dicots whereas evidence of the second type is common
among annual herbaceous species.

GENETIC CONTROL OF REFILLING MECHANISM
Bay leaf tree, Laurus nobilis is an aromatic shrub in which mechanism of refilling is proposed to be linked to starch to sugar conversion. Reserve carbohydrate depletion from xylem parenchyma
induces phloem unloading in a radial manner via ray parenchyma
(Salleo et al., 2009; Nardini et al., 2011). Xylem-phloem solute
exchange has been found to occur along both symplastic and
apoplastic paths (Van Bel, 1990). It has been hypothesized that
solutes might move radially along the ray cell walls, enter the
embolized xylem conduits and increase the solute concentration
of the residual water within them, thus promoting xylem refilling
by altering osmoticum. The role of xylem parenchyma in refilling
is significant. Lianas, shrubs and vine fibers are often observed
to have living protoplasts and starch granules (Fahn and Leshem,
1963; Brodersen et al., 2010). Repeated cycles of embolism and
repair are correlated to cyclic depletion of starch in xylem during drought (Salleo et al., 2009; Secchi et al., 2011). Debatably,
repeated cycles of embolism formation and repair may disable
the refilling mechanism and ultimately lead to carbon starvation
(Sala et al., 2010, 2012; McDowell, 2011). The hydrolyzed starch
movement from xylem is yet unresolved.
Water stressed Populus trichocarpa plants revealed an upregulation of ion transporters, aquaporins, and carbon metabolism
related genes (Secchi et al., 2011; Secchi and Zwieniecki, 2012).
A putative sucrose-cation co-transporter may aid the refilling
process as suggested by the chemical profiling of vessel lumen.
Grapevine refilling petioles show strong upregulation of carbon
metabolism and aquaporin expression (Perrone et al., 2012).

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Sengupta and Majumder

A basic assumption is made that in dicots, to enhance refilling ability trait, one might target carbohydrate metabolizing
genes in a localized manner to improve sucrose release. Sucrose
may be used as an osmoticum inside non-functional lumens or
may be used as energy currency. Localization of increased aquaporins (PIPs and TIPs) within axial parenchyma surrounding
conduits may prove important. It is now proved by imaging studies (Brodersen et al., 2010) that living cells play a central role in
embolism refilling and restoring transport, and by further prevention of air seed and pathogen by sealing off conduits with tyloses.
Further detailed work is needed to identify the stress signals that
mediate talk between xylem vessels and parenchyma.
In monocots, root pressure is the most important mechanism
for refilling reported till date. Grasses exhibit root pressure more
often, and with the increase of plant height the basal root pressure
increases (Cao et al., 2012). Monocots do not exhibit secondary
thickening and ray cells thus the osmoticum and sucrose transport theory do not apply to monocots (Andre, 1998). Selection
for root pressure in these species solves the embolism repair problem and negates the need for carbohydrate transport along the
pathway common in woody angiosperms (Brodersen et al., 2013).
However, Stiller et al. (2005) showed the presence of “novel”
refilling in rice in presence of high negative pressure and suggested
that in upland or low-rainfed rice this mechanism can serve side
by side of a positive root pressure. Root pressure may involve
a stronger mechanical tissue, and whether or not any trade-off
between safety and efficiency is involved is unclear. Study of more
vascular function mutants in monocot crops may resolve the
genes involved in this process.

GENOMIC PERSPECTIVE: GENES, PROTEINS AND MODELS
IMPLICATED IN REFILLING
The battle with cavitation is fought either with efficient refilling or fine structural modulation of pit membrane and strength
of vascular cylinder wall. The genomic, transcriptomic and proteomic studies may thus come under two broad sections: genomic
basis of refilling and genomic basic of mechanical strength
(Figure 2A).

GENOMIC BASIS OF REFILLING
The process of refilling or repair of embolism requires pumping
water in an air-filled cavity. Physically this will require an empty
or air-filled vessel, functional neighbor vessels, a source of energy
to drive the refilling and a source of water to refill. In the previous
sections, the physical and physiological components of embolism
repair have been discussed in detail. However, a reductionist biologist looks further beyond for the possible identities of molecular
candidates that repair the non-functional vessel. It is hypothesized that refilling is a result of an intricate interaction of xylem
parenchyma, (even possibly phloem), vessel wall chemistry, and
the composition and flexibility of pit membranes (Holbrook and
Zwieniecki, 1999). The signals that are sensed when embolism
occurs and the cascades that follow the primary signal transduction event, involve interconnected molecular regulators; that
has been subject of several studies. The most recent model of
refilling puts forward a role of sugar signaling in embolism sensing and refilling mechanism, the involved gene families being
Aquaporins, Sucrose transporters and enzymes related to starch
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Genomics of plant vasculature

breakdown, Alpha and Beta Amylase (Secchi and Zwieniecki,
2010).

AQUAPORINS
Aquaporins are conservedly implicated in the refilling process of
angiosperms and gymnosperms from the very beginning. The
refilling of vessels in Populus trichocarpa is accompanied by selective upregulation of PIPs (Plasma Membrane Intrinsic Proteins).
Secchi et al. (2011) proposed that the sensing of embolism and
accomplishment of refilling is mediated by sugar signals, specifically sucrose. According to their proposed model, when a vessel
is filled with air, free passage of sucrose to the vessel lumen
is hindered, and the sucrose molecules are deposited on vessel wall. This, with a positive feedback loop generate a cascade
of high starch to sucrose conversion (Bucci et al., 2003; Salleo
et al., 2004; Regier et al., 2009). The increased sucrose pool would
be maintained by upregulation of amylases and sugar transporters. Secchi et al. (2011) showed a distinct upregulation in
aquaporins and sucrose transporter (PtSuc 2.1) in air injected or
artificially high osmotica-treated vessels. Ptsuc2.1 shows a high
homology to walnut sucrose transporter, which, on upregulation is able to relieve freeze-thaw induced embolism (Decourteix
et al., 2006). The increased sucrose and the upregulation of aquaporins are correlated spatially and temporally, but connections
are difficult to establish. The model hence proposed is schematically represented in Figure 2B. Almeida-Rodriguez et al. (2011)
showed a gene expression profile of 33 Aquaporins in fine roots
of hybrid poplar saplings and compared light and high transpiration induced vascular hydraulics physiology with respect
to Aquaporin expression. Dynamic changes were observed in
expression pattern of at least 11 aquaporins from poplar; and
some of them were localized in the root tissue. In Arabidopsis,
Postaire et al. (2010) showed that, hydraulic conductivity of
excised rosettes and roots are correlated wih expression of aquaporins. AtPIP1; 2, AtPIP2;1, and AtPIP2;6 are the most highly
expressed PIP genes in the Arabidopsis rosette (Alexandersson
et al., 2005) and under long night, AtPIP1;2 knockout plants
loose 21% hydraulic conductivity in the rosette(Postaire et al.,
2010). The disturbed hydraulics phenotype is a genetic dissection of the direct relation between aquaporin expression and
plant water transport; although there may be components other
than Aquaporin that may serve an important role (Sack and
Holbrook, 2006; Heinen et al., 2009). It has been shown in
hybrid poplar Populus trichocarpa × deltoides, increasing evaporation from leaf surface and perturbed hydraulics is correlated
with high aquaporin expression (Plavcová et al., 2013). In common grapevine, Vitis vinifera L. (cv Chardonnay) inhibitors of
aquaporin-mediated transport greatly affects both leaf hydraulic
conductance and stomatal conductance (Pou et al., 2013). Of 23–
28 Aquaporin isoforms in grapevine, a subset including VvPIP2;2,
VvTIP1;1 plays important role during early water stress, while
VvPIP2;1, VvPIP2;3, VvTIP2;1 are highly expressed during recovery(Pou et al., 2013). In Maize roots, radial water transport are
diurnally regulated by proteins from the PIP2 group (Lopez et al.,
2003). It is evident, though, that not all aquaporins participate in the refilling process. The sugar signal initiation is one
important component; as originally described by Secchi et al.
(2011) and must induce embolism-related aquaporin isoforms.
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Sengupta and Majumder

FIGURE 2 | (A) The strategies of vascular plant in a battle against embolism.
Monocots often employ root pressure, while dicots employ novel refilling
mechanism, and mechanical resistance to resist cavitation. There is no clear
demarcation between the strategies employed by the two groups, and the
strategies may overlap. (B) The sugar sensing model of embolism refilling
process, modified from Secchi et al. (2011). For detail explanations of the
model, refer text and Secchi et al. (2011). Briefly, when vessels are filled and
functional, a default “switch off” mode is active. Sucrose is continuously
transported from accompanying xylem parenchyma cells into the vessels.

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Genomics of plant vasculature

Cavitation induces a “switch on” mode of sensing. When a vessel is filled with
air, free passage of sucrose to the vessel lumen is hindered, and the sucrose
molecules are deposited on vessel wall. This, with a positive feedback loop
generates a cascade of high starch to sucrose conversion (Bucci et al., 2003;
Salleo et al., 2004; Regier et al., 2009). The increased sucrose pool would be
maintained by upregulation of amylases and sugar transporters. The genes
up/downregulated during the sensing process are mentioned in the figure.
Abbreviations used: Xv(F), Xylem Vessel Filled; Xv(E), Xylem Vessel Embolized;
Xp, Xylem Parenchyma. Other abbreviations are explained in the figure.

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The transcriptomic studies show that a very high number of
Carbohydrate Metabolism related genes were upregulated during
embolism (Secchi et al., 2011). Upregulation of the disaccharide
metabolism gene group was observed, along with downregulation
of monosaccharide metabolism; that suggests an accumulation
of sucrose pool on the vessel wall (Secchi et al., 2011). Further
upregulation of ion transporters and downregulation of carbohydrate transporters build up an osmoticum inside the cell to
facilitate efflux of water. Figure 2B (inset) shows a summary of
the number of gene categories showing differential expression
during embolism (Secchi et al., 2011). The energy required for
the pumping in comes from starch hydrolysis and one can presume, xylem specific isoforms of aquaporin, Starch synthetase
and sucrose transporters will be highly expressed during refilling in plants. For critical evaluation of the model parameters,
and its feasibility across the plant kingdom we extracted all
aquaporin gene sequences from Arabidopsis and the Arabidopsis
homologs of Populus trichocarpa sucrose transporters and amylases implicated in embolism Secchi et al., 2009, 2011; Secchi and
Zwieniecki, 2010, 2012, 2013, 2014. The accession numbers of the
fetched Arabidopsis genes are presented in Tables 1A,B. We subjected the gene sequences to protein-protein interaction network
interaction analysis in String software in Expasy, without suggested functional neighbors (Szklarczyk et al., 2010). Generated
interaction network for Arabidopsis gene subsets (mentioned in
Table 1) clearly shows three interaction network clusters, connected to each other (Figure 3), the middle cluster (termed ‘a’
in Figure 3) shows evidenced network of PIPs as well as a RD28,
dehydration stress related protein. Two other clusters (b and c in
Figure 3) exhibit sucrose transporters and NIPs. Amylases form
an un-joined node (d in Figure 3). We further localized the genes
in Arabidopsis publicly available transcriptome analysis database
in different tissues and observed shared enrichment in root endodermis, cortex and stele using e-northern (Figure 4A, Toufighi
et al., 2005). A co-expression profile (Figure 4B) was obtained
using string software, and the common n-mers present in the
genes to induce a co-expression in certain tissues has been analyzed using promomer tool (Figure 4C; Table 2, Supplementary
Table 1, Toufighi et al., 2005). Many of the enriched cis-elements
contribute to dehydration and sugar stress. Overall, the genomic
and transcriptomic data and candidate-gene based data emphasizes the high probability of sugar sensing of embolism. Secchi
and Zwieniecki (2014) also showed that in hybrid poplar, downregulation of PIP1 delimits the recovery of the plant from waterstress-induced embolism, and thus is probably manages the vulnerability of xylem in negative pressure under control condition.
The sugar content in the plant tissue strengthens the view further
(Secchi and Zwieniecki, 2014).

TRANSCRIPTION FACTORS
The corregulation of sugar metabolism and water transport
pathways require a complex transcriptional switch. Indeed, a
large number of transcription factors control the refilling process, and they may regulate the diurnal pattern, the temporal
accuracy and spatial distribution of the pathways involved. The
role of TFs is shared; However, a look at the cis elements of

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Genomics of plant vasculature

pathway components may elucidate the nature of such sharing.
The transcription factors important for xylogenesis and probably
embolism are: AP2/EREBP, bZIP, C3HHD-ZIPIII, NAC, MYB,
bHLH, WRKY, AP2/ERF, WRKY, HD, AUX/IAA, ARF, ZF,
AP2, MYC, (Arabidopsis); HD-ZIPIII, MYB, MADS, and LIM
in Populus, MYB and Hap5a in Pine and HRT in Hordeum
(Dharmawardhana et al., 2010). With the onset of genomic
approaches, much more intensive analysis have been made possible. In a comprehensive genome-wide transcriptome analysis
of P. trichocarpa, with snapshots from each elongating internode from a sapling stage (Internode1 through Internode11) a
large number of differential representation of transcription factors have been obtained (Dharmawardhana et al., 2010). No less
than 1800 transcription factors were readily detectable in at least
one growth phase, of which, 439 are differentially regulated during xylogenesis (Dharmawardhana et al., 2010); some of which
are represented in Table 3. Another study identified 588 differentially changed transcripts during shoot organogenesis in Populus
(Bao et al., 2009, 2013). While the refilling process is majorly
governed by sugar and dehydration signaling, NAC and Myb
TF families remain singularly important in both xylem maturation and lignin biosynthesis. Aspects of xylogenesis that may be
linked with mechanical-functional trade-off of vascular bundle
revolve around lignin. There have been studies on genomics and
transcriptomics of xylogenesis and secondary wood formation;
however the genes responsible to maintain integrity of the vascular cylinder are not clearly known. In Supplementary Table 2, a
comparative snapshot of some selected transcripts and emanating
studies revealing the xylogenesis transcriptome in gymnosperms
and angiosperms is provided. Several recent studies address the
genomics of xylogenesis excellently; some of which are summarized in Table 4.

CAVITATION RESISTANCE INTRODUCED BY PIT MEMBRANE
The major key of cavitation resistance is pit membrane adaptation. To survive, ultrastructure of pit membrane needs to balance
between minimizing vascular resistance and limiting invasion by
pathogen and microbes. While the first is favored by thin and
highly porous membrane, the later needs thick membrane and
narrower pores. This calls for a trade-off between water transport
function and biotic invasion resistance.
The thickness range of the pit membranes in the angiosperms
is very broad, almost 70–1900 nm and so are the diameter of
the pores (10–225 nm). Species with thicker pit membrane and
smaller pores prevent seeding and embolism more successfully
and thus may represent the group of species which has higher
drought resistance.
Pit membrane porosity is not the only determinant of air bubble propagation among conduits. The other factor which serve
equally important role is the contact angle between pit membrane and air water interface. This particular property is a direct
function of pit membrane composition. The more hydrophobic
the membranes are the more the contact angle and subsequently
lower the pressure needed for air-seeding. Additionally, high
lignin content, though required for mechanical strength, interrupt with the hydrogeling of pectins. Pectic substances can swell

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Table 1A | Genes, families and members important in refilling experimentally reported in Populus trichocarpa.
Gene families

Aquaporins

Specific genes
Family

Subfamily

Gene name

JGIv2.0 annotation
name

Arabidopsis homologs

PIP (Plasma Intrinsic
Protein)

PoptrPIP1

PoptrPIP1.1

POPTR_0008s06580

For analysis, the entire aquaporin
family of Arabidopsis has been used
instead of only specific homologs,
refer to Table 1B.

PoptrPIP1.2

POPTR_0003s12870

PoptrPIP1.3

POPTR_0010s19930

PoptrPIP1.4

POPTR_0006s09920

PoptrPIP1.5

POPTR_0016s12070

PoptrPIP2

Alpha-beta amylases

Alpha-amylase

Beta amylase

Sucrose transporters

PoptrAMY

PoptrBMY

Sucrose transporter

PoptrPIP2.1

POPTR_0006s09910

PoptrPIP2.2

POPTR_0009s13890

PoptrPIP2.3

POPTR_0004s18240

PoptrPIP2.4

POPTR_0016s09090

PoptrPIP2.5

POPTR_0010s22950

PoptrPIP2.6

POPTR_0006s12980

PoptrPIP2.7

POPTR_0008s03950

PoptrPIP2.8

POPTR_0009s01940

PtAMY1

POPTR_0515s00220

AT4G25000

PtAMY2

POPTR_0002s01570

AT1G76130

PtAMY3

POPTR_0010s10300

AT1G69830

PtBMY1a

POPTR_0008s17420

AT3G23920

PtBMY1b

POPTR_0001s11000

AT3G23920

PtBMY2

POPTR_0003s10570

AT5G45300

PtBMY3

POPTR_0008s20870

AT5G18670

PtBMY4

POPTR_0003s08360

AT2G02860

PtBMY5

POPTR_0017s06840

AT1G09960

PtSUC2.1

POPTR_0019s11560

AT5G55700

PtSUT1.2

POPTR_0013s11950

AT4G15210

PtSUT2.a

POPTR_0008s14750

AT1G22710

Gene ID data compiled from Secchi et al. (2011); TAIR and phytozome public database.

or shrink in presence or absence of water and thus they control the porosity of membranes. Polygalacturonase mutants in
Arabidopsis showed a higher P50 value (−2.25MPa), suggesting a
role for pectins in vulnerability to cavitation (Tixier et al., 2013).
Mechanically stronger pit membranes thus may resist stretching
and expansion of pore membranes indicating a compromise in
function. Water stress has been reported to exhibit a direct relation to low lignin synthesis (Donaldson, 2002; Alvarez et al., 2008)
although it is not known whether this low lignin help the water
transport better.

SUGGESTED GENETIC BASIS OF CAVITATION RESISTANCE
BY PIT MEMBRANE MODULATION AND MECHANICAL
SUPPORT
Identification of genes and proteins behind the structural and
mechanical controls of pit membrane formation has not progressed so far as repair mechanism of embolism is concerned.
Genetic aspects of plant hydraulics are little studied, since most of
the xylem studies are done in woody trees and study of herbaceous

Frontiers in Plant Science | Plant Genetics and Genomics

crops is rather scant. It is hard to obtain mutants in trees as
the generation time is high, and the study process is long and
laborious. Also, hydraulics in plants is not a simple structural
or functional trait but is a complex physiological phenomenon.
Figuring out the multitrait control switch of this function is thus
difficult.

CAN LIGNIN BIOSYNTHESIS BE CONSIDERED AS A
CONTROL SWITCH?
Among the living cell processes that may take active part in
controlling hydraulics, lignin biosynthesis is a major candidate
and highly deciphered. In chemical nature, it is a polymer of
phenylpropanoid compounds synthesized through a complex
biosynthetic route (Figure 5; Hertzberg et al., 2001; Vanholme
et al., 2010). Luckily enough, the genes on the metabolic grid are
sequenced in plants like Arabidopsis and Populus, which is helpful to understand their modulation under stress. Till date, both
biotic and abiotic stressors have been implicated in modulation
of lignin biosynthesis, as well as seasonal, developmental and

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Table 1B | The entire aquaporin family in Arabidopsis extracted from TAIR.
Gene family name
Delta tonoplast integral protein family

Accession
At1g31880

Major intrinsic protein, putative

At1g80760

Nodulin-like protein

At1g73190

Tonoplast intrinsic protein, alpha (alpha-TIP)

At2g45960

Aquaporin (plasma membrane intrinsic protein 1B)

AT3g06100

Putative major intrinsic protein

AT5g47450

Membrane channel protein-like; aquaporin (tonoplast intrinsic protein)-like

AT3g53420

Plasma membrane intrinsic protein 2a

At2g36830

Putative aquaporin (tonoplast intrinsic protein gamma)

At2g37170

Aquaporin (plasma membrane intrinsic protein 2B)

At2g37180

Aquaporin (plasma membrane intrinsic protein 2C)

AT4g35100

Plasma membrane intrinsic protein (SIMIP)

At2g29870

Putative aquaporin (plasma membrane intrinsic protein)

At1g01620

Plasma membrane intrinsic protein 1c, putative

AT3g61430

Plasma membrane intrinsic protein 1a

AT3g54820

Aquaporin/MIP–like protein

At1g17810

Tonoplast intrinsic protein, putative

AT3g47440

Aquaporin-like protein

At2g16850

Putative aquaporin (plasma membrane intrinsic protein)

At2g39010

Putative aquaporin (water channel protein)

AT3g16240

Delta tonoplast integral protein (delta-TIP)

At1g52180

Aquaporin, putative

AT4g23400

Water channel–like protein

At2g25810

Putative aquaporin (tonoplast intrinsic protein)

AT4g00430

Probable plasma membrane intrinsic protein 1c

AT5g37810

Membrane integral protein (MIP)–like

AT5g37820

Membrane integral protein (MIP)–like

AT4g17340

Membrane channel like protein

AT4g10380

Major intrinsic protein (MIP)–like

varietal changes (Anterola and Lewis, 2002; Zhong and Ye,
2009). Representing a large share of non-fossil organic carbon
in biosphere, lignification provides mechanical support and
defends the plant against pests and pathogens. The mechanical support, further, is mostly linked to xylem vessels and
hydraulics.
Lignin is made from monolignols (hydroxy-cinnamyl alcohol), sinapyl alcohol, coniferyl alchol, and p-coumaryl alcohol
in a smaller quantity. The complex metabolic grid and the transcriptional switches are described in details elsewhere (Hertzberg
et al., 2001). The major metabolic pathway channeling into
this grid is phenylpropanoid pathways through phenylalanine
(Phe). Phe, synthesized in plastid through shikimic acid biosynthesis pathway, eventually generates p-coumaric acid by the
activity Phenylalanine Ammonia-Lyase (PAL) and Cinnamate
4-Hydroxylase (C4H). p-coumaric acid empties itself into the
lignin biosynthesis grid to result into three kinds of lignin
units; guaiacyl (G), syringyl (S), and p-hydroxyphenyl (H)
units. Gymnosperm lignin polymer is majorly composed of
G and H units, angiosperms show G and S units and H is
elevated in compressed softwood and grasses (Boerjan et al.,
2003).

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TIGR Protein Type

There are stresses in nature that change plant lignin content.
For example, lignin amount in Picea abies is predicted to correlate positively with annual average temperature (Gindl et al.,
2000). Temperate monocots as well show an increase of lignin in
response to increasing temperature (Ford et al., 1979). In Triticum
aestivum, 2◦ C chilling stress decreases leaf lignin but increases in
root is observed (Olenichenko and Zagoskina, 2005). Curiously,
some studies have shown that although no changes in the levels of
lignin or its precursors were observed in plants maintained at low
temperatures, there was an increase in related enzyme activities
as well as an increase in gene expression. Cold acclimatization in
Rhododendron shows upregulation of C3H, a cytochrome P450dependent monooxygenase without further functional characterization (El Kayal et al., 2006). It has been argued that expression
of C3H could result in changes in the composition of lignin, altering the stiffness of the cell wall albeit without a definitive proof.
The basal part of the maize roots show a growth reduction and
low plasticity of cell wall associated with upregulation of two
genes in lignin grid (Fan et al., 2006) in response to drought. The
increase of free lignin precursors in the xylem sap and reduced
anionic peroxidase activity in maize has been associated with low
lignin synthesis in drought (Alvarez et al., 2008). It is possible that

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FIGURE 3 | The protein-protein interaction network of Arabidopsis sucrose transporters, amylases and aquaporins, generated using String database.
Thicker lines indicate stronger reaction (Szklarczyk et al., 2010).

reducing lignin may directly affect the vascular tissue, encouraging water transport, lowering air seeding and increasing cavitation
resistance; however it is not known what share of reduced lignin
actually amount to stem vasculature, water column support and
pit membrane plasticity.

BIOTECHNOLOGICAL MODIFICATION OF LIGNIN
METABOLISM
With the advancement of genomic data, it is now possible to
map the genetic changes which may influence hydraulic architecture. However, the model systems are questionable. Among the
woody plant species, the genome of poplar has been sequenced;
and the lignin biosynthesis network is fully characterized in
Arabidopsis and rice. It is expected that change in lignin content
may result differently in herbaceous and woody plants. There are
controversial results obtained so far. In free-standing transgenic
poplar trees, a 20–40% reduction in lignin content was associated
with increased xylem vulnerability to embolism, shoot dieback
and mortality (Voelker et al., 2011). Similarly the severe inhibition of cell wall lignification produced trees with a collapsed
xylem phenotype, resulting in compromised vascular integrity,

Frontiers in Plant Science | Plant Genetics and Genomics

and displayed reduced hydraulic conductivity and a greater susceptibility to wall failure and cavitation (Coleman et al., 2008). A
study on the xylem traits of 316 angiosperm trees in Yunnan, and
their correlations with climatic factors claimed that wood density
and stem hydraulic traits are independent variables (Zhang et al.,
2013).
A weak pipeline and less lignification compromises vascular
integrity as observed from the above results. On the other hand,
low lignin helps to increase the plasticity of the pit membrane
pectin. Thus compromising lignin quantity may have serious
impact on strength of the vascular cylinder; on the other hand,
it may increase the pit membrane hydrophilic property and may
offer resistance toward cavitation.
Lately, Arabidopsis has been taken in as a model for secondary
tissue development, although it lacks formation of secondary
wood. Tixier et al. (2013) argued that Arabidopsis might be as well
considered to be a model of xylem hydraulics. They regarded the
inflorescence stem of A. thaliana as a model for xylem hydraulics
despite its herbaceous habit, as it has been shown previously
that the inflorescence stem achieves secondary growth (Altamura
et al., 2001; Ko et al., 2004), allows long-distance water transport

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Sengupta and Majumder

FIGURE 4 | (A) Localization of the genes from Tables 1, 2 in various
Arabidopsis tissue, from public microarray databases, and e-northern tool at
Botany Array Resource (Toufighi et al., 2005). (B) Co-expression profile of the
genes in Arabidopsis (Szklarczyk et al., 2010). (C) Distribution of relevant

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Genomics of plant vasculature

n-mers in the promoters of the above genes. That may induce shared
expression. The results are generated using String and Promomer tools in
Botany Array Resource (Toufighi et al., 2005). A tabulated form of the results
are presented in Supplementary Table 5.

May 2014 | Volume 5 | Article 224 | 42

Sengupta and Majumder

Genomics of plant vasculature

Table 2 | Representative common n-mer details over represented in the embolism with respective transcription factors and their probable
roles.
n-mers

Z-score

Regulation mode

Probable role

Consensus matches to n-mer in the PLACE 25.0.1 database

AAAT**

3.5

Positive

Dehydration responsive

Matched AAAT at offset 4 in CACTAAATTGTCAC 14BPATERD1: “14
bp region” (from −599 to −566) necessary for expression of erd1
(early responsive to dehydration) in dehydrated Arabidopsis

ATAA**

4.0

Positive

Sugar responsive

Matched ATAA at offset 2 in ACATAAAATAAAAAAAGGCA
−314MOTIFZMSBE1: located between −314 and −295 region of
maize (Z.m.) Sbe1 gene promoter; critical positive cis element;
important for the high-level, sugar-responsive expression of the
Sbe1 gene in maize endosperm cells; recognized by nuclear protein

ATAT**

2.7

Positive/negative

MADS domain

Matched [AT][AT][AT][AT] at offset 5 in TTDCCWWWWWWGGHAA
AGAMOUSATCONSENSUS: binding consensus sequence of
Arabidopsis (A.t.) AGAMOUS MADS domain

AATA

3.3

Positive

Sugar-responsive

Matched AATA at offset 6 in ACATAAAATAAAAAAAGGCA
−314MOTIFZMSBE1: Located between −314 and −295 region of
maize (Z.m.) Sbe1 gene promoter; critical positive cis element;
important for the high-level, sugar-responsive expression of the
Sbe1 gene in maize endosperm cells; recognized by nuclear protein

TTAT

3.1

Positive

Sugar responsive, binding
activity to Myb core

Matched AATA at offset 6 in ACATAAAATAAAAAAAGGCA
−314MOTIFZMSBE1: located between −314 and −295 region of
maize (Z.m.) Sbe1 gene promoter; critical positive cis element;
important for the high-level, sugar-responsive expression of the
Sbe1 gene in maize endosperm cells; recognized by nuclear protein;
matched TATT at offset 2 in
TTTATTTACCAAACGGTAACATC23BPUASNSCYCB1: “23 bp UAS
(Upstream activating sequence)” found in the promoter of Nicotiana
sylvestris (N.s.) CycB1 gene; located between −386 and −409;
contains a 5 bp element identical to the MYB binding core (ACGT);
required for M-phase-specific expression; binds protein complexes
in a cell cycle-regulated manner

ATCA**

4.5

Positive/negative

MADS domain, homeobox
binding domain

Matched [AT][AT][ACGT][ACGT] at offset 8 in
NTTDCCWWWWNNGGWAAN AGL1ATCONSENSUS: binding
consensus sequence of Arabidopsis (A.t.) AGL1 (AGAMOUS-like 1);
AGL1 contains MADS domain; see S000339; AGL20 is a MADS
domain gene from Arabidopsis that is activated in shoot apical
meristem during the transition to flowering; AGL20 is also regulated
by the Gibberellin pathway; complex regulatory net works involving
several MADS-genes underlie development of vegetative structures

GAAG**

4.0

Positive

ABA-responsive, MADS

Matched GAAG at offset 6 in ATGTACGAAGC ABAREG2: motif
related to ABA regulation; gene: sunflower helianthinin; transacting
factor: bZIP? Matched [ACGT][ACGT][AT][ACGT] at offset 0 in
NNWNCCAWWWWTRGWWAN AGL2ATCONSENSUS: binding
consensus sequence of Arabidopsis (A.t.) AGL2 (AGAMOUS-like 2);
AGL2 contains MADS domain; AGL2 binds DNA as a dimer

CGAA

2.4

Positive

ABA-responsive

Matched CGAA at offset 5 in ATGTACGAAGC ABAREG2: motif
related to ABA regulation; gene: sunflower helianthinin; transacting
factor: bZIP?

An html table for all n-mers is presented in Supplementary Table 1. **denotes overrepresentation.

from the roots to the aerial parts of plant, and experience gravity
and other mechanical perturbations (Telewski, 2006). There are
distinct similarities between woody dicots and Arabidopsis inflorescence stems with respect to vessel length and diameter as well

Frontiers in Plant Science | Plant Genetics and Genomics

as presence of simple perforation plates and border (Sperry et al.,
2005; Hacke et al., 2006; Schweingruber, 2006; Wheeler et al.,
2007; Christman and Sperry, 2010). It has a genetic potential to
develop ray cells and rayless wood is observed in juvenile trees

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Sengupta and Majumder

Table 3 | Some representative transcription factors in Populus

Genomics of plant vasculature

Table 4 | Representative transcriptome studies in literature.

trichocarapa Xylem Maturation (Dharmawardhana et al., 2010).
Xylogenesis

Embolism

Lignin biosynthesis

DRE binding protein (DREB1A)

Li et al., 2013

Secchi et al., 2011 Hertzberg et al., 2001

Ethylene responsive element binding factor

Carvalho et al., 2013

Zhong et al., 2011

Putative AP2 domain transcription factor

Pesquet et al., 2005

Lu et al., 2005

Ethylene responsive element binding factor 4 (aterf4,9)

Li et al., 2012

Schrader et al., 2004

Homeodomain–like protein.1

Dharmawardhana et al., 2010

Auxin response transcription factor (ARF1,9)

Karpinska et al., 2004

WRKY family transcription factor

Bao et al., 2009

ATPAO4 (POLYAMINE OXIDASE 4); amine oxidase

Rengel et al., 2009

Ethylene-responsive transcriptional coactivator

Mishima et al., 2014

Lateral root primordia (LRP1)

Plavcová et al., 2013

Transcription factor TINY, putative

Zhong et al., 2011

WRKY family transcription factor

MADS-box protein
Putative CCCH-type zinc finger protein
bHLH protein/contains helix-loop-helix DNA binding motif
Zinc finger protein Zat12
WRKY family transcription factor
BEL1-like homeobox 4 protein (BLH4)
TINY-like protein
Myb family transcription factor
Putative squamosa-promoter binding protein
Putative transcription factor/similar to transcription factor SF3
ES43 like protein/ES43 protein
AP2 domain protein RAP2.1
Abscisic acid responsive elements-binding factor (ABF3)
bHLH protein/contains helix-loop-helix DNA binding motif
Myb family transcription factor
CCAAT-binding transcription factor subunit A (CBF-A)

(Carlquist, 2009; Dulin and Kirchoff, 2010). Having Arabidopsis
as a full proof model for woodiness may open numerous possibilities. The best among them are study of environmental stresses
on hydraulic characters. A number of mutants can be generated
and screened in Arabidopsis with deviant safety vs. efficiency phenotype with little effort. The Arabidopsis thaliana irregular xylem
4 phenotype (irx4) a mutant for cinnamoyl-CoA reductase 1
(CCR1) gene, has provided us with valuable insight in the role
of lignin reduction and associated phenotypic changes in vasculature. As reported by Jones (2001), near-half decrease of lignin
component with no associated change in cellulose or hemicellulose content gives the plant an aberrant vascular phenotype.
Most of the cell interior is filled up with expanded cell wall and
the xylem vessels collapse. Abnormal lignin gives the cell wall
a weak ultrastructure and less structural integrity (Jones et al.,
2001; Patten et al., 2005). Later it has been claimed that by modulating the CCR gene, irx4 mutant has obtained a delayed albeit
normal pattern of lignification program (Laskar et al., 2006).
It thus has to be borne in mind that not only the content but
the spatio-temporal pattern of lignin deposition may change the
xylem ultrastructure and change the safety-efficiency trade-off
limit.
There are a few transcriptional control switches in lignin
production which can be used in modification of vascular

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conductance. Modulation of co-ordinate expression of cellulose and lignin in rice is an important study regarding such
transgene opportunities. Expression of the Arabidopsis SHN2
gene (Aharoni et al., 2004) under a constitutive promoter
in rice alters its lignocellulosic properties along with introduction of drought resistance and enhanced water use efficiency (Karaba, 2007). The Arabidopsis SHINE/WAX INDUCER
(SHN/WIN) transcription factor belongs to the AP2/ERF TF
family, and besides wax regulation, control drought tolerance in Arabidopsis (Aharoni et al., 2004; Broun et al., 2004;
Kannangara et al., 2007). Expression analysis of cell wall biosynthetic genes and their putative transcriptional regulators shows
that moderated lignocellulose coordinated regulation of the
cellulose and lignin pathways which decreases lignin but compensates mechanical strength by increasing cellulose. All the
processes ascribed to master control switch SHN may be directed
toward evolution of land plants; waxy cover to lignin synthesis for erect disposition and water transport. However, no
xylem irregularities are seen in this mutant (Aharoni et al.,
2004).
As the best studied pathway related to secondary cell wall formation, lignin biosynthesis should offer the best metabolic grid
that can be tweaked in plants to genetically understand mechanical functional trade-off and resistance to cavitation. General
reduction of PAL (Phenylalanine ammonia lyase, E.C. 4.3.1.5)
activities in developing plants may be one possible point of interest. PAL is a “metabolic branch- point” where Phe is directed
toward either lignins or proteins (Rubery and Fosket, 1969).
However, according to Anterola et al. (1999, 2002) and other such
studies there are other pathways originating from pentose phosphate or glycolysis that may directly end into lignin biosynthesis
and PAL may not serve as rate limiting step at all. Cinnamate
4-hydroxylase (C4H) is another candidate that has been downregulated with decrease in overall lignin content, however, with no
effect on vascular integrity or function (Fahrendorf and Dixon,
1993; Nedelkina et al., 1999). p-Coumarate-3-hydroxylase (C3H)
in Arabidopsis (CYP98A3) may be necessary and rate-limiting
step in the monolignol pathway (Schoch et al., 2001). Its expression is correlated with the onset of lignification and a mutant
line results in dwarfed phenotype with reduced lignin (Schoch

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Sengupta and Majumder

FIGURE 5 | Simplified scheme for monolignol synthesis. The main
pathway in dicotyledonous plants is highlighted in black, involving
phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H),
4-coumarate CoA ligase (4CL), p-hydroxycinnamoyl-CoA: quinate shikimate
p-hydroxycinnamoyltransferase (HCT), p-coumarate 3-hydroxylase (C3H),

et al., 2001). Cinnamoyl CoA O-methyltransferase (CCOMT), 4coumarate:CoA ligase (4CL), cinnamoyl CoA reductase (CCR),
and cinnamyl alcohol dehydrogenase (CAD) isoforms are downstream pathways in monolignol formation, and their relation to
vascular integrity are yet to establish, though phenotypes associated with their mutations are tall/dwarf stature, altered lignin
composition, and reduced mechanical support. Conclusive data
are yet to be obtained from these studies.

CONCLUSION
Hydraulic safety margin in a plant is clearly driven by its phylogenetic origin. Conifers have developed minimal hydraulic
resistance which is a necessity for water transport through short
unicellular tracheids. The unique torus-margo anatomy of the
conifer pit membrane let them adaptively overpower multicellular vessels in angiosperms in certain cases. Conifer stems are
proposed to have larger hydraulic safety margins when compared
with most angiosperm stems (Meinzer et al., 2009; Choat et al.,
2012; Johnson et al., 2012) although it is also suggested that they
recover poorly from drought-induced embolism (Brodribb et al.,
2010). The refilling mechanisms vary greatly between monocots
and dicots and herbaceous and woody plants. Resistance to cavitation is thus closely related to many factors: such as nature of
the mechanical tissue, the vasculature, the height of the plant,
the systematic position of the plant, developmental stage and
stresses the plant must face. It can be further emphasized that
though, in certain dicots a trade-off within the water transport ability and mechanical strength (efficiency vs. safety) has
been observed, the genomic factors which may control the tradeoff are not identified till date completely; and the observation
is far from universal. The two major physiological phenomena
which seem to be linked to embolism resistance are lignification and solute transport between xylem parenchyma, vessel

Frontiers in Plant Science | Plant Genetics and Genomics

Genomics of plant vasculature

caffeoyl-CoA O-methyltransferase (CCOMT ), hydroxycinnamyl-CoA reductase
(CCR), ferulate 5-hydroxylase (F5H), caffeate O-methyltransferase (COMT),
and cinnamyl alcohol dehydrogenase (CAD). Alternate pathways are in light
gray. H subunits are only minor lignin components in dicots. Adapted from
Quentin et al. (2009).

and phloem. The genes and proteins behind these physiological traits are many, and even the obtained transgenic plants
and mutants have only been scantily characterized. The effects
of assembly of the components are poorly understood and the
models proposed do not address all plant families universally.
Overall, although a phylogenetic trend is observed among the
plants for the evolutionary establishment of hydraulic safety margins, the mechanisms behind have not been understood enough
till date to predict the molecular basis and evolution in genomic
scale. However, the best metabolic pathway to offer advantageous biotechnological outputs appears to be the lignin synthesis network, which should be assessed by mutant screening as
well as by tissue specific overexpression studies in the plant. In
case of monocots, drought-induced root- specific overexpression may be of advantage in generating better crops, as root
pressure seems to be the major regulator. Crop biotechnology
is largely benefitted when the gene pool and their interaction
behind a biological process is better known. Overexpressing
aquaporins along with the sugar sensing network under a
dehydration-responsive promoter could be a formidable strategy
to prevent embolism-induced wilting. An approach toward modulation of lignin biosynthesis grid regulation may yield better
woody, or even herbaceous crops. The overwhelming knowledge emanating from transcriptomic and genomic studies build
the platform where biologists can attempt crop modification for
such complex traits as vascular integrity and water transport,
without or marginally limiting other beneficial traits, in near
future.

ACKNOWLEDGMENTS
Sonali Sengupta thanks the Fast-Track Young Scientist Award
Program of the Department of Science and Technology and
the Department of Biotechnology, Government of India, for

May 2014 | Volume 5 | Article 224 | 45

Sengupta and Majumder

support. Arun Lahiri Majumder is a Raja Ramanna Fellow of the
Department of Atomic Energy, Government of India. We cordially thank Dr. Harald Keller, Senior Scientist, INRA, France,
for his kind permission to reproduce the lignin biosythetic pathway figure from his publication, appropriately cited. We further
thank the reviewers for their valuable comments which helped us
to improve the manuscript.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online
at: http://www.frontiersin.org/journal/10.3389/fpls.2014.00224/
abstract

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 12 February 2014; accepted: 05 May 2014; published online: 28 May 2014.
Citation: Sengupta S and Majumder AL (2014) Physiological and genomic basis of
mechanical-functional trade-off in plant vasculature. Front. Plant Sci. 5:224. doi:
10.3389/fpls.2014.00224
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Sengupta and Majumder. This is an open-access article distributed
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REVIEW ARTICLE
published: 03 June 2014
doi: 10.3389/fpls.2014.00244

Integrating omic approaches for abiotic stress tolerance in
soybean
Rupesh Deshmukh , Humira Sonah , Gunvant Patil , Wei Chen , Silvas Prince , Raymond Mutava ,
Tri Vuong , Babu Valliyodan and Henry T. Nguyen *
National Center for Soybean Biotechnology and Division of Plant Sciences, University of Missouri, Columbia, MO, USA

Edited by:
Rajeev K. Varshney, International
Crops Research Institute for the
Semi-Arid Tropics, India
Reviewed by:
Paula Casati, Centro de Estudios
Fotosinteticos-CONICET, Argentina
Iain Robert Searle, The University of
Adelaide, Australia
*Correspondence:
Henry T. Nguyen, National Center for
Soybean Biotechnology and Division
of Plant Sciences, University of
Missouri, 1-31 Agriculture Building,
Columbia, MO 65211-7140, USA
e-mail: nguyenhenry@missouri.edu

Soybean production is greatly influenced by abiotic stresses imposed by environmental
factors such as drought, water submergence, salt, and heavy metals. A thorough
understanding of plant response to abiotic stress at the molecular level is a prerequisite for
its effective management. The molecular mechanism of stress tolerance is complex and
requires information at the omic level to understand it effectively. In this regard, enormous
progress has been made in the omics field in the areas of genomics, transcriptomics,
and proteomics. The emerging field of ionomics is also being employed for investigating
abiotic stress tolerance in soybean. Omic approaches generate a huge amount of data,
and adequate advancements in computational tools have been achieved for effective
analysis. However, the integration of omic-scale information to address complex genetics
and physiological questions is still a challenge. In this review, we have described
advances in omic tools in the view of conventional and modern approaches being used
to dissect abiotic stress tolerance in soybean. Emphasis was given to approaches such
as quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and
genomic selection (GS). Comparative genomics and candidate gene approaches are also
discussed considering identification of potential genomic loci, genes, and biochemical
pathways involved in stress tolerance mechanism in soybean. This review also provides a
comprehensive catalog of available online omic resources for soybean and its effective
utilization. We have also addressed the significance of phenomics in the integrated
approaches and recognized high-throughput multi-dimensional phenotyping as a major
limiting factor for the improvement of abiotic stress tolerance in soybean.
Keywords: abiotic stress tolerance, soybean, genomics, proteomics, transcriptomics, ionomics, phenomics

INTRODUCTION
Soybean is the most important legume crop which provides
sources of oil and protein for human as well as for livestock.
Soybean also enhances soil fertility because of the symbiotic nitrogen fixing ability. Soybean contributed to more than 50% of
globally consumed edible oil (SoyStats, 20131 ). Apart from the
consumption, soybean oil is being considered as a future source
of fuel and efforts are being made to improve soy-diesel production (Candeia et al., 2009). Soybean protein-based bio-degradable
materials are also being considered as an alternative for plastics (Song et al., 2011). Soybean products are gaining attention
because of its pharmaceutical attributes such as anti-cancerous
properties (Ko et al., 2013). Such diverse uses of soybean make
it a more widely desired crop plant and are rapidly increasing its demand. In this regard, soybean yield improvement has
been achieved by 1.3% per year (Ray et al., 2013). However, the
increasing global population will need double the current food
production by the year 2050 and at the current rate it can achieve
only ∼55% (Ray et al., 2013). It may be more difficult to produce sufficient yield with the changing climate. Therefore soybean
yield prediction must consider the ongoing challenges of extreme
1 Available online at: http://www.soystats.com (Accessed December 10, 2013).

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weather such as drought, flood, heat, cold, frost, and possible UV
stress.
Abiotic stresses are the most challenging of all major constraints in crop production. Soybean production is not only
influenced by environmental factors, such as drought, water submergence, salt, and heavy metals, but it also faces challenges
to get adapted in non-traditional areas. This demands extensive
breeding for the development of local cultivars (Tanksley and
Nelson, 1996; Grainger and Rajcan, 2013). Direct selection for
yield stability based on multi-location trials has been traditionally used for the development of varieties adapted to adverse
environmental conditions. This approach is more difficult for abiotic stress related traits because of low heritability and highly
influenced by environmental conditions (Manavalan et al., 2009).
Direct selection is also a time-consuming and labor intensive process. Strategic marker-assisted breeding can efficiently accelerate
the development of tolerant cultivars; however, it also necessitates knowledge about genomic loci governing the traits and the
availability of tightly linked molecular markers (Xu et al., 2012).
Molecular marker development has been accelerated with the
availability of sequenced genomes and organelles in crop plants
(Singh et al., 2010; Sonah et al., 2011a; Tomar et al., 2014).
Marker-assisted breeding has become sophisticated with the
availability of complete soybean genome sequence due to
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subsequent development of locus-specific molecular markers
(Schmutz et al., 2010; Song et al., 2010). Genome-wide high
density markers availability also facilitates the haplotype analysis
and identification of different alleles for agronomical important traits (Tardivel et al., 2014). Marker-assisted breeding has
been carried-out mostly for simple traits governed by a single, or at most a few loci (Shi et al., 2009; Jun et al., 2012).
Marker-assisted breeding also suffers due to undesired genetic
drag (Tanksley and Nelson, 1996; Shi et al., 2009). The genetic
background of the recurrent parent also plays an important role
in the phenotypic expression of newly introgressed gene(s) mostly
because of the complex epistatic interaction (Palloix et al., 2009).
In the case of multiple complex traits, epistatic interaction is
more unpredictable and it is hard to develop a strategic breeding plan until unless solid information is available about the
molecular mechanisms involved in the trait development. Recent
technological development in genomics provides tremendous
power to predict genetic factors, their evolution, distribution,
and interactions at great extent (Morrell et al., 2011; Sonah
et al., 2011b). Genetic engineering is the most advanced approach
that has been used for the genetic improvement of soybean.
Genetically modified (GM) soybean crops for insect-resistance
and herbicide-tolerance has covered most of the cultivated area in
the world (Carpenter, 2010). Although, GM soybean has proven
to be very successful, it raises ethical controversies, and it is
available only for few traits (Carpenter, 2010). Integration of
multi-disciplinary knowledge is required to design future soybean
varieties with ideal plant types providing high and stable yield in
adverse climatic conditions. In this context, a detailed review was
made to evaluate progress achieved in different omic approaches
and to highlight future perspectives for its effective exploration toward the development of abiotic stress tolerant soybean
cultivars.

thousands of simple sequence repeat (SSR) markers and millions
of single nucleotide polymorphism (SNP) markers (Song et al.,
2010; Sonah et al., 2013). Recent developments in next generation sequencing (NGS) technologies make sequencing-based
genotyping cost effective and efficient. Three main complexity
reduction methods, namely Reduced Representation Libraries
(RRLs), Restriction site Associated DNA (RAD) sequencing,
and Genotyping-by-Sequencing (GBS) are being routinely used.
Among these, GBS is gaining more attention because of its
simplified and cost effective methodology (Elshire et al., 2011;
Sonah et al., 2012). The GBS approach has been successfully
used in several crop species (Poland and Rife, 2012). Recently,
GBS methodology has been improved and streamlined for soybean (Sonah et al., 2013). However, sequencing-based genotyping
methods require computational expertise and significant time for
data analysis. This restricts its use in marker-assisted breeding
where timely selection is very important. GBS will be widely used
in the future with an increasing number of software packages and
computational pipelines (Sonah et al., 2013).
Technological advances have also provided a high-throughput,
reliable, and quick array-based genotyping platforms. The SNP
array development require initial information about SNPs, fortunately, information about millions of SNPs is already available in the public domain (Table 1). The Illumina Infinium
array (SoySNP50K iSelect BeadChip) for ∼50,000 SNPs has
been successfully developed and used for the genotyping of several soybean plant introduction (PI) lines (Song et al., 2013).
Technological advances beyond this make it possible to resequence hundreds of lines in a cost effective manner and has
started a new era of genotyping by re-sequencing (Lam et al.,
2010; Li et al., 2013; Xu et al., 2013). Now, the challenge for
plant biologists is how to effectively use these resources for
marker-assisted applications.

OMICS APPROACHES IN THE TECHNOLOGICAL ERA

QTL MAPPING FOR ABIOTIC STRESS TOLERANCE IN SOYBEAN

Plant molecular biology aims to study cellular processes, their
genetic control, and interactions with environmental changes.
Such a multi-dimensional and detailed investigation requires
large-scale experiments involving entire genetic, structural, or
functional components. These large scale studies are called
“omics.” Major components of omics include genomics, transcriptomics, proteomics, and metabolomics (Figure 1). These
omics approaches are routinely used in various research disciplines of crop plants, including soybean. Omics approaches
have improved very rapidly during the last decade as technology advances. Subsequently, high-throughput data developed by
omic experiments require extensive computational resources for
storage and analysis. Thus, several online databases, analysis
servers, and omics platforms have been developed. Omics is getting broader coverage and it is anticipated that several new omic
fields will evolve in near future.

Genetic fingerprinting, linkage mapping, and quantitative trait
loci (QTL) mapping are marker based applications that have
become more sophisticated with the availability of different
genotyping platforms (Table 1). Consequently, several efforts
have been made to identify QTL for abiotic stress tolerance
in soybean (Table S1). QTL studies have identified thousands
of QTL spanning the entire genome (www.soykb.org, www.
soybase.org). This is due to the complex inheritance of abiotic
stress tolerance which has identified unstable QTL across different environments. Further utilization of QTL information for
marker-assisted breeding or candidate gene identification has
become difficult due to this complexity. Statistical tools such
as “Meta-QTL analysis” have been advanced that compile QTL
data from different studies together on the same linkage map
for identification of precise QTL region (Deshmukh et al., 2012;
Sosnowski et al., 2012). Several efforts have been performed to
identify meta-QTL for different agronomical and quantitative
traits in soybean (Table 2). Meta-analysis studies are still required
exclusively for abiotic traits.

GENOMICS ADVANCES FOR ABIOTIC STRESS TOLERANCE
IN SOYBEAN
MOLECULAR MARKER RESOURCES

Genomic applications in soybean have become more standard
with the availability of whole genome sequence (WGS) (Schmutz
et al., 2010). The WGS provided the basis for the development of
Frontiers in Plant Science | Plant Genetics and Genomics

GENOME-WIDE ASSOCIATION STUDIES (GWAS) IN SOYBEAN

QTL mapping using bi-parental populations has limitations
because of restricted allelic diversity and genomic resolution.
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FIGURE 1 | Important branches of omics with their major components being used in different integrated approaches in soybean.

Table 1 | List of significant studies performed to develop SNP markers and subsequent genotyping using different technological platforms in
soybean.
Sr. No

Genotyping platform/Approach

Genotypes

1

Illumina GoldenGate assay

3 RIL mapping populations

384

Hyten et al., 2008

2

Illumina Infinium SoySNP6K BeadChip

92 RILs

5376

Akond et al., 2013

3

Illumina genome analyzer/Reduced
Representation Libraries (RRLs)

5 diverse genotypes

14,550

Varala et al., 2011

4

Illumina GoldenGate assay

3 RIL mapping populations

5

Illumina genome analyzer /RRLs

444 RILs

25,047

Hyten et al., 2010a

6

Illumina GAIIx/Genotyping by sequencing
(GBS)

8 diverse genotypes

10,120

Sonah et al., 2013

7

Illumina Genome Analyzer II/whole genome
re-sequencing

17 wild and 14 cultivated

8

Illumina Genome Analyzer II/whole genome
re-sequencing

25 diverse genotypes

9

Illumina genome analyzer/RRLs

Parental lines of mapping population

39,022

Wu et al., 2010

10

Illumina Infinium BeadChip

96 each of landraces, elite cultivars and wild
accessions

52,041

Song et al., 2013

The allelic diversity can be increased to some extent by
using multi-parental crosses. Recently, Multi-parent Advanced
Generation Inter-Cross populations (MAGIC) has been used
to identify QTL for blast and bacterial blight resistance,
salinity and submergence tolerance, and grain quality traits
in rice (Bandillo et al., 2013). Such multi-parental populations has mapping resolution limitations since it depends on
meiotic events (crossing-over) (Kover et al., 2009). In contrast, the genome-wide association study (GWAS) approach
provides opportunities to explore the tremendous allelic
diversity existing in natural soybean germplasm. Mapping
resolution of GWAS is also higher since millions of crossing

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SNPs

References

1536

Hyten et al., 2010b; Vuong et al.,
2010

2,05,614
51,02,244

Lam et al., 2010
Li et al., 2013

events have been accumulated in the germplasm during
evolution.
GWAS is routinely being used in many plant species, but only
a few studies have been reported in soybean (Table S2). These
studies were performed with limited markers and genotypes.
GWAS in soybean is lagging behind compared to maize, mostly
because of the slow linkage disequilibrium (LD) decay (Hyten
et al., 2007; Mamidi et al., 2011). Another serious problem is the
confounding population structure since it may cause spurious
associations leading to an increased false-discovery rate (FDR).
Studies that involve case-control phenotypes (binary) carefully
relate the cases and controls to minimize confounding effects.

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Table 2 | Meta-QTL studies performed for different traits in soybean.
Sr. No

Trait

Meta QTL

QTL compiled

Studies compiled

References

1

Soybean cyst nematode resistance

7

62

17

2

Soybean cyst nematode resistance

16

151

19

Zhang et al., 2010

3

Seed oil content

20

121

22

Qi et al., 2011b
Qi et al., 2011a

Guo et al., 2006

4

Seed oil content

25

130

39

5

100-seed weight

17

65

12

Zhao-Ming et al., 2009

6

100-seed weight

15

117

13

Sun et al., 2012a

7

Fungal disease resistance

23

107

23

Wang et al., 2010

8

Insect resistance

20

81

–

Jing et al., 2009

9

Seed protein content

23

107

29

Zhao-Ming et al., 2011

10

Plant height

12

93

13

Sun et al., 2012b

11

Phosphorus efficiency

29

96

–

Huang et al., 2011

12

Growth stages

9

98

10

Qiong et al., 2009

GWAS for quantitative traits like abiotic stress tolerance are predictable to be affected by a confounding population. Different
models have been developed for population stratification and
spurious allelic associations like MLM and CMLM which takes
into account the population structure and kinship. Recently,
GWAS for Sclerotinia sclerotiorum resistance was performed using
7864 SNPs in soybean (Bastien et al., 2014). The study provided
details of a probable marker requirement and methodologies
involving population stratification for effective GWAS (Bastien
et al., 2014). Development in statistical tools, genotyping methods, and studies involving larger sets of genotypes will definitely
improve GWAS power in soybean.
GENOMIC SELECTION (GS) IN SOYBEAN

Marker-assisted breeding for simple Mendelian traits are easy
and effective, but it can be problematic for the complex traits
such as abiotic stresses that are generally polygenic. Even major
QTLs can explain only a small fraction of phenotypic variation
and may show unexpected trait expression in new genetic backgrounds because of epistatic interactions. These limitations can be
effectively addressed by the use of an approach called “Genomicselection” (GS). GS is relatively simple, more reliable, and a more
powerful approach where breeding values of lines are predicted
using their phenotypes and marker genotypes (Heffner et al.,
2009). GS is more effective since it uses all marker information
simultaneously to develop a prediction model avoiding biased
marker effects (Heffner et al., 2009). GS captures small-effect QTL
that governs most of the variation including epistatic interaction
effects.
An overview of research articles regarding GS published during last decade showed exponential growth within recent years
(Figure S1). The increasing popularity of GS among plant as
well as animal breeders is mostly because of the reduced cost of
genotyping. Currently, GS is being used for breeding in several
different crops (Table S3). In soybean, efforts have been made to
evaluate GS using different models. A GS study in soybean has
used 126 recombinant inbred lines and 80 SSR markers to predict primary embryogenesis capacity which is a highly polygenic
trait (Hu et al., 2011). In this report, high correlation (r2 = 0.78)
has been observed among the genomic estimated breeding value

Frontiers in Plant Science | Plant Genetics and Genomics

(GEBV) and the phenotypic value. Another study published
recently using 288 cultivars and 79 SSR markers, found a correlation coefficient of 0.90 among the GEBV and the phenotypic value
(Shu et al., 2012). Both the reports have shown high accuracy of
prediction but only with a few markers and genotypes. Predicting
the accuracy of GS will need more investigations involving highthroughput genotyping of larger populations evaluated across
different environments.
Accuracy of GS largely depends on genetic × environmental (G × E) interaction but most of the studies focused only on
an estimation of the main effect for each marker. These multienvironmental trials are of prime importance for plant breeding
not only to study G × E but especially to increase the number of breeding cycles per year. The challenge for GS is to get
accurate GEBV in respect to the G × E effect. Considering environmental effects is not new for plant breeders and most statistical
models used for multi-location trials do reflect G × E (Hammer
et al., 2006). It is also more common in QTL mapping studies
where QTL × environment interaction evaluations were utilized
to estimate QTL effect.
Improved factorial regression models have been proposed
recently for GS that consider stress covariates derived from
daily weather data (Heslot et al., 2014). This model has shown
increased accuracy by 11.1% for predicting GEBV in unobserved
environments where weather data is available (Heslot et al., 2014).
This study suggests possible utilization of phenotypic data and
historical data of weather conditions accumulated over decades
in different soybean breeding programs. Similar information can
be used for abiotic stress tolerance improvement in soybean.
COMBINING MARKER-ASSISTED BREEDING WITH GENOMIC
SELECTION

Molecular marker genotyping is a common requirement for QTL
mapping, GWAS, and GS and can be the basis for combining these
approaches (Figure 2). Most of the GS studies have used recombinant inbred line (RIL) populations to train the prediction model
(Table S3). Therefore, GS and QTL mapping can be performed
simultaneously. A set of diverse cultivars can be used for GWAS
and GS all together (Table S3). In the marker-assisted breeding, introgression of QTL or GWAS loci to well adapted cultivar

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Abiotic stress tolerance in soybean

effective management of abiotic stress. Transcriptome profiling
provides an opportunity to investigate plant response regulation and to identify genes involved in stress tolerance mechanisms. Earlier, approaches using expressed sequence tags (ESTs)
sequencing along with several techniques, such as suppression
subtractive hybridization (SSH), have been extensively used for
transcriptome profiling of soybean under abiotic stress conditions (Clement et al., 2008). In addition, information of ESTs
have been used to develop spotted microarrays (O’Rourke et al.,
2007). These techniques are efficient but do not ensure analysis
of entire genes in the soybean genome. Several high-throughput
techniques have been developed for transcriptome analysis due
to the advancement in sequencing technology and the availability of the whole soybean genome sequence, (Libault et al., 2010;
Schmutz et al., 2010; Cheng et al., 2013). These platforms have
been extensively used for transcriptome profiling to uplift abiotic
stress tolerance mechanisms in soybean (Table 3).
Microarray is a high-throughput technology where thousands
of probes representing different genes are hybridized with RNA
samples. Using the hybridization signal level, gene expression
is calculated. The Affymetrix GeneChip representing 61K probe
sets is routinely being used for transcriptome profiling of soybean under different abiotic stresses (Haerizadeh et al., 2011; Le
et al., 2012). The normalized expression data generated using the
Affymetrix GeneChip can be used to compare soybean experiments performed across the world. An expression database has
been developed to globally explore public and proprietary expression data (www.genevestigator.com). The microarray data represents various tissues, developmental stages, and environmental
conditions (Table 3). Effective analysis of such tremendous data
using sequence homology and functional annotation will be
helpful to understand biological processes.
FIGURE 2 | Combined approach of QTL mapping/Genome-wide
association study (GWAS) and Genomic selection (GS).

is performed. The donor line (for QTL or GWAS loci) may be
wild or low yielding line. Therefore, several cycles of backcrossing
are performed to retain the genetic background of the recipient parent (the adapted cultivar) except for the QTL/GWAS loci
which represent the donor background. Nevertheless, GS does
not provide control over the genetic background and this may be
problematic when the donor is not an adapted line. In addition,
GS cannot guarantee for major QTL which are already known.
Therefore, information about QTL/GWAS loci should be incorporated with GS models so that the balance of genetic background
can be made along with maximum gain of breeding value.

TRANSCRIPTOME PROFILING FOR ABIOTIC STRESS
TOLERANCE
Plants, including soybean, responses to external environments is
very complex. A wide range of defense mechanisms are activated
that increases plant tolerance against adverse conditions in order
to avoid damage imposed by abiotic stresses. The first step toward
stress response is stress signal recognition and subsequent molecular, biochemical, and physiological responses activated through
signal transduction (Komatsu et al., 2009; Ge et al., 2010; Le
et al., 2012). Understanding such responses is very important for
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RNA-Seq, AN ADVANCED APPROACH FOR TRANSCRIPTOME
PROFILING

Cost effective and high-throughput sequencing technologies
make it possible to analyze transcriptomes by sequencing, known
as RNA-seq. The RNA-seq approach has several advances over the
microarray technology where available genomic information is
used to design probe sets. However, RNA-seq does not require
gene information and is capable of identifying novel transcripts
that were previously unknown and also provides opportunities
to analyze non-coding RNAs. The relative accuracy of microarrays and RNA-Seq has been evaluated using proteomics and
it has been shown that RNA-Seq provides a better estimate
of absolute expression levels (Fu et al., 2009). Applications of
RNA-seq can be expanded further with an increased understanding of molecular regulations. For instance, RNA-seq is being
used for transcription start site mapping, strand-specific measurements, gene fusion detection, small RNA characterization,
and detection of alternative splicing events (Ozsolak and Milos,
2010).
RNA-Seq has been performed to investigate seven tissues and
seven stages in seed development in soybean (Severin et al., 2010).
This effort has generated an expression atlas for soybean genes
which serves as a useful resource. The tissue specific expression
pattern of genes is helpful in understanding regulation and tissue
specific function.
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Table 3 | Major transcriptomic analysis for the abiotic stress tolerance in soybean using different technological platforms.
Sr. No. Trait/tissue

Platform

DEG*

Key points

References

1

Soybean root development/root
tips and non-meristematic tissue

Affymetrix chips containing
37,500 probe sets

9148

Haerizadeh et al., 2011

2

Iron stress/root from isogenic
lines

Custom array containing 9728
cDNAs

48

3

Drought stress at late
developmental stages/V6 and R2
stages under drought and control

61 K Affymetrix Soybean Array
GeneChip

3276 for V6
3270 for R2

4

Herbicide resistance/plant under
atrazine and bentazon stress

6646

5

Saline-alkaline stress
tolerance/NaCl and NaHCO3
treatments
Flooding stress

cDNA microarray
with 36,760 different cDNA
clones
AffymetrixSoybean GeneChip

HiCEP (29,388) high coverage
expression profiling

97 genes
and 34
proteins

Resource of novel target
genes for further studies
involving root development
and biology
Genes involved in DNA repair
and RNA stability were
induced
Expression of many GmNAC
and hormone-related genes
was altered by drought in V6
and/or R2 leaves
Expression of genes related
to cell recovery, such
ribosomal components
Genes with altered
expression regulated by
alkaline stress
Combined approach with
proteomics

6

9027

O’Rourke et al., 2007

Le et al., 2012

Zhu et al., 2009

Ge et al., 2010

Komatsu et al., 2009

*Differentially expressed genes.

COMBINING QTL MAPPING, GWAS, AND TRANSCRIPTOME PROFILING

QTL mapping and GWAS are very effective approaches to identify
chromosomal region(s) associated with a particular phenotype.
However, QTL spans large segments of chromosomes and it is also
the same for GWAS where LD decay is slow as in case of soybean
(Hyten et al., 2007). QTL or GWAS loci possess hundreds of genes
that make the identification of candidate genes difficult (Sonah
et al., 2012). This is similar in transcriptome profiling where thousands of genes have been found to be differentially expressed even
with genetically similar isogenic lines (Table 3). Therefore combining QTL mapping or GWAS with transcriptome profiling will
complement each other. For instance, candidate genes for grain
number QTL in rice have been identified using microarray based
transcriptome profiling of recombinant inbreed lines with contrasting phenotypes (Deshmukh et al., 2010; Sharma et al., 2011;
Kadam et al., 2012). Similarly, a pair of soybean near-isogenic
lines (NILs) differing in seed protein and an introgressed QTL
segment (∼8.4 Mb) have been used to study variation in transcript abundance in the developing seed (Bolon et al., 2010).
The study identified 13 candidate genes in the QTL region using
the Affymetrix Soy GeneChip and high-throughput Illumina
whole transcriptome sequencing (Bolon et al., 2010). A combined
approach of mapping and transcriptome profiling is based on an
assumption that the quantitative trait is regulated by differential
expression of candidate genes. This is not always true. Most of
the time sequence variation present in candidate genes may cause
defective proteins (Xu et al., 2013). Therefore, re-sequencing of
QTL locus along with transcriptomics will also be a valuable
approach to compliment mapping efforts.

PROTEOMICS IN SOYBEAN
Proteomics deals with structural and functional features of all
the proteins in an organism. It is important to understand

Frontiers in Plant Science | Plant Genetics and Genomics

complex biological mechanisms including the plant responses
to abiotic stress tolerance. Abiotic stress tolerance mechanisms
involve stress perception, followed by signal transduction, which
changes expression of stress-induced genes and proteins. Posttranslational changes are also important in plant responses to
abiotic stresses. A single gene can translate in several different
proteins and a few genes can lead to a diverse proteome. Such
inconsistency limits genomics and transcriptomic approaches
more specifically, when post translational changes govern phenotype. Differential expression observed at the transcriptional
(mRNA) level need not be translated into differential amounts
of protein. To address this, several proteomic studies have been
performed to understand abiotic stress tolerance mechanisms in
soybean (Table S4).
Unexpected levels of changes in the soybean proteome can
occur during stress response and these changes can lead to different defense mechanisms. Some common proteins involved in
redox systems, carbon metabolism, photosynthesis, signaling, and
amino acid metabolism have been found to be associated with
various stress responses in soybean (Zhen et al., 2007; Aghaei
et al., 2009; Yamaguchi et al., 2010; Qin et al., 2013). These candidate proteins can directly link to genetic regulation of stress
response in soybean. Candidate protein information can be used
for the functional annotation of genes present in QTL regions or
found differentially expressed under stress conditions.
In the near future, various proteomics approaches will be
routinely used in soybean research that will generate tremendous information regarding structural and functional attributes
of proteins. A systematic cataloging of information in the form
of a publically accessible database is very important. Recently, a
proteome database has been developed that contains reference
maps of the soybean proteome collected from several organs, tissues, and organelles (Mooney and Thelen, 2004; Brechenmacher

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Deshmukh et al.

et al., 2009; Ohyanagi et al., 2012). Presently, these reference maps
comprised information of about 3399 proteins from seven organs
and 2019 proteins from four subcellular compartments that
were identified using two-dimensional electrophoresis (http://
proteome.dc.affrc.go.jp/soybean/). Volunteer deposition of proteomic information in such databases is necessary for effective
utilization of available knowledge for the management of abiotic
stress tolerance in soybean.

METABOLOMICS ADVANCES FOR ABIOTIC STRESS
Metabolomic studies in plants aim to identify and quantify the
complete range of primary and secondary metabolites involved
in biological processes. Therefore metabolomics provides a better
understanding of biochemical pathways and molecular mechanisms. The knowledge of genes, transcripts and proteins involved
cannot alone help to understand the biological process completely until knowledge of metabolites that are involved becomes
available.
Several metabolomics studies have been performed to understand biochemical processes in soybean (Table S5). Development
of new chromatographic and mass spectrometric platforms along
with the enhancement of operational and analytical capabilities
of existing platforms revolutionizes metabolomic investigations
both in plant and animal sciences. The platforms such as gas
chromatography mass spectrometry (GC-MS), fourier transform
ion cyclotron resonance mass spectrometry (FT-ICR-MS), liquid chromatography mass spectrometry (LC-MS), capillary electrophoresis mass spectrometry (CE-MS), and nuclear magnetic
resonance (NMR) are routinely used in plant sciences (Putri et al.,
2013). Capability, limitations and specificity of these techniques
has been recently reviewed in terms of effective utilization of these

Abiotic stress tolerance in soybean

advanced resources (Putri et al., 2013). In-depth accurate analyses of metabolite information including the spectral data are
the major challenge for the use of high-throughput techniques.
Several statistical models and bioinformatics programs have been
developed to analyze the metabolome in an interactive manner
(Fernie et al., 2011; Putri et al., 2013).

IONOMICS IN SOYBEAN
Ionomics is the study of elemental composition of an organism that mostly deals with high-throughput identification and
quantification. Ionomics is important to understand element
composition and their role in biochemical, physiological functionality and nutritional requirements of plants. Phosphorus (P)
and potassium (K) are the two key elements used as macronutrients in fertilizer to ensure better crop yield. However plants
require many other elements and those are not uniformly distributed among different soil types. Plants have evolved with a
diverse element uptake ability at different locations because of
diverse soil types (Fujita et al., 2013). This justifies the need of
integrating ionomics with genomics to explore existing genetic
differences. An ionomic study has been performed to analyze
concentrations of 17 different elements in diverse accessions and
three RIL populations of Arabidopsis thaliana grown in several
different environments (Buescher et al., 2010). Significant differences in elemental composition between the Arabidopsis accessions were detected and more than hundred QTL were identified
for different elemental accumulation (Buescher et al., 2010). Most
of the ionomics studies to date in soybean have been performed
to analyze nutritive value of soybean products (Table S6).
The elemental composition of a plant is controlled by multiple
factors including element availability, uptake capability of roots,

FIGURE 3 | Phenomics and its integration with other omics approaches.

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Deshmukh et al.

transport, and external environment which regulate physiological processes such as evapotranspiration. Because of such factors,
the plant ionome has become very sensitive and specific so that
the element profile reflects different physiological states. Recently
a study performed in barley has analyzed ionome of wild accessions and cultivar differing in salt tolerance, grown in presence of
150 and 300 mM NaCl (Wu et al., 2013) and observed decreased
amounts of K, magnesium (Mg), P and manganese (Mn) in roots
and K, calcium (Ca), Mg and Sulfur (S) in shoots at the seedling
stage. In addition, significant negative correlation among the
amount of accumulated Na and metabolites involved in glycolysis and tricarboxylic acid (TCA) cycle have been observed (Wu
et al., 2013). This ionomic study suggests the possible rearrangement of elemental profiles and metabolic processes to modify the
physiological mechanisms of salinity tolerance.
Improvement in abiotic stress tolerance with the application of
several inorganic element has been observed (Liang et al., 2007;
Pilon-Smits et al., 2009). For instance, silicon (Si) has shown
beneficial effects against different abiotic stresses including high
salinity, water stress, heavy metal stress, and UV-b (Liang et al.,
2007). Previously, soybean has been considered as poor accumulator of silicon mostly because of the genetic differences existing
in the germplasm and very few genotypes have been evaluated
to draw this conclusion (Hodson et al., 2005). However, with the
advancement in ionomics technologies, silicon transporter genes
have been identified recently in soybean using the integrated
omics approach (Deshmukh et al., 2013). This study has used
computational genomics, transcriptomics, and ionomics information available in the model plant species such as Arabidopsis
and rice. Besides this, high-throughput efforts for maximum
number of elemental profiles in soybean in respective external
environment are required. That will definitely improve the understanding of the soybean ionome and its subsequent utilization in
the management of abiotic stress tolerance.

PHENOMICS PROSPECTIVE IN SOYBEAN
The phenotype is a physical and biochemical trait of an organism. Phenomics is a study involving high-throughput analysis of
phenotype. Phenotype is the ultimate resultant from the complex
interactions of genetic potential between an organism and environment. Precision phenotyping is important to understand any
biological system. In plant as well as animal sciences, a particular phenotype (as symptoms) is used to understand biological
status, such as disease, pest infestation or physiological disorders. With technological advances, genomic resources have been
routinely used to predict phenotype based on the evaluation of
genetic markers; it can be called “genetic symptoms.” The success
of genomics is based on how reliable connection is there between
a genetic marker and the phenotype. In plant breeding, genetic
improvement through omics approaches is being conducted to
achieve ideal phenotype that will ensure higher and stable yield
under diverse environmental conditions. Therefore phenomics
integrated with other omics approaches has the most potential
in the plant breeding (Figure 3).
Phenome has a broader meaning than what is being generally
considered. It is not limited to the visible morphology of an
organism but expectedly larger and complex. Unlike genomics,

Frontiers in Plant Science | Plant Genetics and Genomics

Abiotic stress tolerance in soybean

where the entire genome can be characterized by sequencing, the
phenome cannot be characterized entirely. Therefore, the term
phenomics being an analogy to genomics expected only study of
particular set of phenotype at high-throughput level and not the
entire set. In this regards, the technological development in image
processing and the automation techniques have played important roles. Plant imaging with light sources from visible to near
infrared spectrum provides an opportunity for non-destructive
phenotyping. Therefore, real-time analysis of plant development
became possible. Moreover, robotic technologies used in phenomic platforms have increased the precision and speed of phenotyping. This has allowed for incorporating additional aids
such as precise irrigation and fertilization systems. For instance,
“PHENOPSIS” an automated phenomic platform has been developed to study water stress in Arabidopsis and has a robotic arm
loaded with a tube for irrigation and a camera (Granier et al.,
2006). These types of advanced phenomic platforms have been
developed and made available for wider range of crop plants
(www.lemnatec.com). However, these platforms have not gained
the expected popularity even though tremendous advancement in
both imaging as well as robotic technology has been achieved.
In soybean, several phenomic efforts have been performed but
most of these are pilot experiments (Table S7). Recently, a method
has been developed to assess leaf growth in soybean under different environmental conditions (Mielewczik et al., 2013). This
method can utilize different light sources that are available in
a greenhouse as well as under field conditions. Marker tracking approaches (Martrack Leaf) have also been used to facilitate
accurate analysis of two-dimensional leaf expansion with high
temporal resolution (Mielewczik et al., 2013). Apart from this,
phenomics has been used to facilitate efficient identification of
soybean cultivars which is very important for germplasm resource
management and utilization (Zhu et al., 2012). Zhu et al. (2012),
used a laser light back-scattering imaging technology to analyze
single seed. Images of laser light illuminated the soybean seed
surface were captured by a charge-coupled device (CCD) camera.
The characteristic pattern of laser luminance is analyzed by image
processing technology to identify a particular cultivar. Such characteristic of laser light back-scattering can be used to assess quality
and other seed characteristics as markers for selection in breeding
programs.
Phenomics in soybean is lagging far behind genomics because
hundreds of genomes and many genetic populations are resequenced. One best example is the 1000 genome re-sequencing
project at the University of Missouri, MO, USA (http://so
ybeangenomics.missouri.edu/news2012.php). The 1000 genome
project will generate a huge amount of genomic information
which will require utilization of comparable phenomic data. This
will be helpful to accelerate soybean research in many ways.

ROLE OF ONLINE DATABASES FOR EFFECTIVE INTEGRATION
OF OMICS PLATFORMS
The recent advancement in the omic platforms has generated tremendous information which has been used to promote
research activities in all possible dimensions. Utilization of available information has become possible because of computational
resources that helps to catalog, store, and analyze available

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Deshmukh et al.

Abiotic stress tolerance in soybean

Table 4 | Online databases exclusively developed to host soybean research data generated from different omics platforms.
Sr. No

Database

Features

Tools

1

SoyBase
SoyBase and the Soybean Breeder’s Toolbox,
USDA and Iowa University, http://soybase.org/

Genetic and physical maps, QTL,
Genome sequence, Transposable
elements, Annotations, Graphical
chromosome visualizer

BLAST search, ESTs search, SoyChip
Annotation Search, Potential
Haplotype (pHap) and Contig Search,
Soybean Metabolic Pathways, Fast
Neutron Mutants Search, RNA-Seq
Atlas

2

SoyKB
Soybean Knowledge Base, University of Missouri,
Columbia, http://soykb.org/

Multi-omics datasets,
Genes/proteins, miRNAs/sRNAs,
Metabolite profiling, Molecular
markers, information about plant
introduction lines and traits,
Graphical chromosome visualizer

Germplasm browser, QTL and Trait
browser, Fast neutron mutant data,
Differential expression analysis,
Phosphorylation data, Phylogeny,
Protein BioViewer, Heatmap and
hierarchical clustering, PI and trait
search, FTP/data download
capabilities

3

SoyDB
Soybean transcription factors database, Missouri
University, http://casp.rnet.missouri.edu/soydb/

Protein sequences, Predicted
tertiary structures, Putative DNA
binding sites, Protein Data Bank
(PDB), Protein family
classifications

PSI-BLAST, Browse database, Family
Prediction by HMM, FTP data retriever

4

SGMD
The Soybean Genomics and Microarray Database,
http://bioinformatics.towson.edu/SGMD/

Integrated view genomic, EST
and microarray data

Analytical tools allowing correlation of
soybean ESTs with their gene
expression profiles

5

Deltasoy
An Internet-Based Soybean Database for Official
Variety Trials,
http://msucares.com/deltasoy/testlocationmap.htm

Official variety trial (OVT)
information in soybean,
Mississippi OVT data, including
yield, location, and disease
information

Comparison tools for variety trail data,
phenotypic data and disease related
data

6

DaizuBase
An integrated soybean genome database including
BAC-based physical maps,
http://daizu.dna.affrc.go.jp/

BAC-based physical map, Linkage
map and DNA markers, BAC-end,
BAC contigs, ESTs, full-length
cDNAs

Gbrowse, Unified Map, Gene viewer,
BLAST

7

SoyMetDB
The soybean metabolome database,
http://soymetdb.org

Soybean metabolomic data

Pathway Viewer

9

SoyProDB
Soybean proteins database,
http://bioinformatics.towson.edu

Several 2D Gel images showing
isolated soybean seed proteins

Search tool for 2D spots, Navigation
tools for protein data

10

SoyGD
The Soybean GBrowse Database, Southern Illinois
University, http://soybeangenome.siu.edu/

Physical map and genetic map,
Bacterial artificial chromosome
(BAC) fingerprint database,
Associated genomic data

Sequence data retrieval tools,
Navigation tool for sequence
information of different builds

11

SoyTEdb
Soybean transposable elements database,
www.soybase.org/soytedb/

Williams 82 transposable element
database

Browse for Repetitive elements,
Transposable Element and Map
position, Data retrieval tools

12

SoyXpress
Soybean transcriptome database,
http://soyxpress2.agrenv.mcgill.ca

Soybean ESTs, Metabolic
pathways, Gene Ontology terms,
Swiss-prot Identifiers and
Affymetrix gene expression data

BLAST search, Microarray
experiments, Pathway search etc

www.frontiersin.org

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Deshmukh et al.

data and make it easily accessible through user friendly interfaces so called “databases.” In this regard, several databases have
been developed for soybean (Table 4). Among these, Soybean
Knowledge Base (SKB, http://soykb.org) is a very useful database
that provides a comprehensive web resource for omics data from
several different platforms (Joshi et al., 2012). The SKB resources
are helpful for bridging soybean translational genomics and
molecular breeding research. It contains information of genes,
proteins, microRNAs, sRNAs, metabolites, molecular markers,
and phenomic information of soybean plant introductions (PI).
It also provides interference to integrate multi-omics datasets and
because of this, a galaxy of information becomes comparable
and more useful. For instance, genes in the QTL region can be
retrieved very easily along with the functional annotations, associated protein information in respect of structure and functional
features, syntenic information with other model plants, sequence
variation among different cultivars, gene expression data including tissue specific variations and many other types of information
for soybean.

GENERAL CONCLUSION
Different omics tools have been employed to understand how soybean plants respond to abiotic stress conditions. We realize that
the studies to integrate multiple omics approaches are limiting in
soybean due to the increased cost and potential challenging integrated omic scale analysis. Recent developments in computational
resources, statistical tools, and instrumentation have lowered the
cost of omics in many folds but integrated analysis needs novel
tools and technical wizards. The comprehensive nature of multiomic studies provides an entirely new avenue and future research
programs should plan to adapt accordingly. In soybean, genomics
and transcriptomics have progressed as expected but the other
major omic branches like proteomics, metabolomics, and phenomics are still lagging behind. These omic branches are equally
important to get clear picture of the biological system. Notably,
phenomic studies need to be extensively employed along with
the other omics approaches. Desired phenotype is ultimate aim
of crop sciences; therefore it needs to be understood intensely.
Different omic tools and integrated approaches discussed in the
present review will provide glimpses of current scenarios and
future perspectives for the effective management of abiotic stress
tolerance in soybean.

ACKNOWLEDGMENTS
The authors are thankful to Theresa Musket and Michelle Keough
for their insight, critical reviews and language improvement. This
research was supported by grants from the United Soybean Board,
USA.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online
at: http://www.frontiersin.org/journal/10.3389/fpls.2014.00244/
abstract

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0010
Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 10 March 2014; accepted: 13 May 2014; published online: 03 June 2014.
Citation: Deshmukh R, Sonah H, Patil G, Chen W, Prince S, Mutava R, Vuong T,
Valliyodan B and Nguyen HT (2014) Integrating omic approaches for abiotic stress
tolerance in soybean. Front. Plant Sci. 5:244. doi: 10.3389/fpls.2014.00244
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Deshmukh, Sonah, Patil, Chen, Prince, Mutava, Vuong,
Valliyodan and Nguyen. This is an open-access article distributed under the terms of
the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are
credited and that the original publication in this journal is cited, in accordance with
accepted academic practice. No use, distribution or reproduction is permitted which
does not comply with these terms.

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REVIEW ARTICLE
published: 08 July 2014
doi: 10.3389/fpls.2014.00323

Virus-induced gene silencing is a versatile tool for
unraveling the functional relevance of multiple
abiotic-stress-responsive genes in crop plants
Venkategowda Ramegowda 1† , Kirankumar S. Mysore 2 and Muthappa Senthil-Kumar 3*
1
2
3

Department of Crop Physiology, University of Agricultural Sciences, GKVK, Bangalore, India
Plant Biology Division, The Samuel Roberts Noble Foundation, Ardmore, OK, USA
National Institute of Plant Genome Research, New Delhi, India

Edited by:
Mukesh Jain, National Institute of
Plant Genome Research, India
Reviewed by:
Vagner Benedito, West Virginia
University, USA
Matthew R. Willmann, University of
Pennsylvania, USA
*Correspondence:
Muthappa Senthil-Kumar, National
Institute of Plant Genome Research,
JNU Campus, Aruna Asaf Ali Marg,
PO Box No. 10531,
New Delhi 110 067, India
e-mail: skmuthappa@nipgr.ac.in
† Present address:
Venkategowda Ramegowda,
Department of Crop, Soil and
Environmental Sciences, University
of Arkansas, Fayetteville, USA

Virus-induced gene silencing (VIGS) is an effective tool for gene function analysis in plants.
Over the last decade, VIGS has been successfully used as both a forward and reverse
genetics technique for gene function analysis in various model plants, as well as crop
plants. With the increased identification of differentially expressed genes under various
abiotic stresses through high-throughput transcript profiling, the application of VIGS is
expected to be important in the future for functional characterization of a large number
of genes. In the recent past, VIGS was proven to be an elegant tool for functional
characterization of genes associated with abiotic stress responses. In this review, we
provide an overview of how VIGS is used in different crop species to characterize genes
associated with drought-, salt-, oxidative- and nutrient-deficiency-stresses. We describe
the examples from studies where abiotic stress related genes are characterized using
VIGS. In addition, we describe the major advantages of VIGS over other currently available
functional genomics tools. We also summarize the recent improvements, limitations and
future prospects of using VIGS as a tool for studying plant responses to abiotic stresses.
Keywords: abiotic stress, functional genomics of crop plants, plant viruses, post-transcriptional gene silencing,
virus-induced gene silencing

INTRODUCTION
The recent advances in next-generation sequencing technology
has enabled sequencing of stress-specific transcriptomes and
genomes of stress tolerant and susceptible cultivars (Morozova
and Marra, 2008). Furthermore, an inventory of genes showing altered expression under several abiotic stresses has been
established for many crop species by expressed sequence tag
(EST) analysis (Gorantla et al., 2007; Wani et al., 2010; Blair
et al., 2011). In contrast to the enormous progress made in
generating sequence information, functional analysis of genes
is lagging behind. Although in silico approaches and comparative genomic strategies have provided initial clues about the
identity and function of abiotic-stress-responsive genes in many
crop species (Gorantla et al., 2007; Tran and Mochida, 2010;
Soares-Cavalcanti et al., 2012), comprehensive functional characterization tools are necessary for understanding the precise role
of these genes in combating abiotic stresses. Mutant plants generated by chemical mutagenesis (Saleki et al., 1993), T-DNA tagging
(Koiwa et al., 2006), and transposon tagging (Zhu et al., 2007)
have been used for understanding stress tolerance. However, the
generation of large-scale mutant populations requires tedious
and laborious efforts, and identification of mutated genes is a
lengthy process. RNAi is another tool used for studying the functional relevance of various abiotic-stress-related genes (Guo et al.,
2002; Senthil-Kumar and Udayakumar, 2010), but this requires

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time-consuming genetic transformation. Therefore, in order to
quickly study the function of a large number of genes identified
through abiotic-stress-specific transcriptome profiles in several
crop species and their wild relatives, alternative high-throughput
tools are needed. Virus-induced gene silencing (VIGS) has
emerged as a successful gene knockdown technique in several
crop species in part because it does not require transformation
(Baulcombe, 1999; Burch-Smith et al., 2004; Senthil-Kumar and
Mysore, 2011a) (Supplementary Table 1). Over the past several
years, VIGS has been successfully used to understand the abiotic
stress tolerance mechanisms in crop plants (Senthil-Kumar and
Udayakumar, 2006; Senthil-Kumar et al., 2008; Manmathan et al.,
2013). In this review, we discuss the utility of this powerful technique to study genes involved in abiotic stress tolerance. We also
discuss the mechanism of VIGS and list the VIGS vectors available
for a wide range of crops and novel ways for application of VIGS
to carry out functional analysis of abiotic-stress-responsive genes.
Further, the recent improvements in VIGS protocol, limitations
and future prospects are discussed.

MECHANISM OF VIGS AND GENESIS OF VIGS VECTORS
VIGS is a post-transcriptional gene silencing (PTGS)-based technique (Baulcombe, 1999), and it exploits the natural defense
mechanisms employed by plants to protect against invading
viruses (Voinnet, 2001). Plants infected by viruses induce double

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stranded RNA (dsRNA) mediated PTGS which degrades viral
RNAs. For VIGS, the viral genomes are modified by removing
genes which induce virus symptoms and cloning the cDNAs of
viral genomes into binary vectors under CaMV35S promoter
along with convenient multiple cloning sites to facilitate insertion of target gene fragments (Voinnet, 2001; Liu et al., 2002a,b).
Viruses that do not have suppressors of gene silencing or have
only weak suppressors are modified as VIGS vectors to induce
PTGS-mediated degradation of target plant mRNAs (Li and Ding,
2001; Cao et al., 2005). VIGS vectors are constructed by cloning
a fragment (usually 300–500-bp) of the plant target gene with
efficient siRNA generation and no off-target genes into the modified viral genome (http://bioinfo2.noble.org/RNAiScan.htm) (Xu
et al., 2006). The recombinant virus is then introduced into
plant cells through Agrobacterium tumefaciens-mediated transient expression or in vitro transcribed RNA inoculation or direct
DNA inoculation (Supplementary Table 2). After the recombinant virus is introduced into plant cells, the transgene is amplified
along with the viral RNA by either an endogenous or a viral
RNA-dependent RNA polymerase (RdRp) enzyme generating
dsRNA molecules (Dalmay et al., 2000; Mourrain et al., 2000).
These dsRNA intermediates are then recognized by DICER-like
enzymes which cleave dsRNA into small interfering RNAs (siRNAs) of 21- to 25-nucleotides (Deleris et al., 2006). The double
stranded siRNAs are then recognized by the RISC complex.
The RISC complex uses the single stranded siRNAs and identifies complementary RNA sequences in the cell and degrades
them (Fagard et al., 2000; Morel et al., 2002) (Supplementary
Figure 1). VIGS has been shown to occur for a shorter period of
approximately 3 weeks and the efficiency decreases after a month
resulting in partial or complete recovery of plants from the silencing (Ratcliff et al., 2001; Hiriart et al., 2003; Ryu et al., 2004)
(Supplementary Figure 2A). However, recent evidences suggest
that some VIGS vectors can be used to maintain the gene silencing
for several months by suitably modifying plant growth conditions that favor viral multiplication (Fu et al., 2006; Tuttle et al.,
2008; Senthil-Kumar and Mysore, 2011b, 2014) (Supplementary
Figure 2B) and can transmit to next generation (Senthil-Kumar
and Mysore, 2011b) behaving like stable transgenic plants
(Supplementary Figure 2C).
To date, about 35 DNA or RNA viruses have been modified as
VIGS vectors (Senthil-Kumar and Mysore, 2011a). The VIGS vector resources available for crop plants are listed in Supplementary
Table 1. Interestingly, the ability of certain viruses to infect a
large number of host plants enabled the use of a single VIGS
vector for gene silencing in several plant species (Robertson,
2004). For example, Tobacco rattle virus (TRV)-based VIGS vector is one of the most widely used VIGS vectors due to its
ability to infect a wide range of host plants, systemic spread
throughout the host plant including meristem, and lack of severe
virus-associated symptoms in the infected plant (Valentine et al.,
2004; Martín-Hernández and Baulcombe, 2008). TRV is a positive single stranded RNA virus with bipartite genome (RNA1
and RNA2). The RNA1 contains genes encoding RNA-dependent
RNA polymerase, movement protein and 16K cysteine rich protein (Macfarlane, 1999). The RNA2 contains gene encoding coat
protein and restriction sites for cloning the gene of interest (Liu

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VIGS for abiotic stress studies

et al., 2002b). Successful TRV-based VIGS requires infiltration of
both RNA1 and RNA2 components. The TRV-based vector has
been successfully demonstrated in functional analysis of abioticstress-responsive genes in model plants like Nicotiana benthamiana (Senthil-Kumar et al., 2007) and crop plants like tomato
(Solanum lycopersicum and S. pimpinellifolium) (Senthil-Kumar
and Udayakumar, 2006; Li et al., 2013; Virk et al., 2013), chili
pepper (Capsicum annuum) (Lee et al., 2010; Choi and Hwang,
2012; Lim and Lee, 2014) and rose (Rosa hybrid) (Dai et al., 2012;
Liu et al., 2013; Jiang et al., 2014).
Another source of VIGS vectors used for silencing of abiotic stress genes are the novel two-component system based on
satellite-viruses along with helper viruses. In nature satelliteviruses are totally dependent on other viruses for replication
(Tao and Zhou, 2004; Cai et al., 2007). An example of the DNA
virus based two-component system is a satellite-virus-based vector, DNAβ, which was used along with Tomato yellow leaf curl
china virus (TYLCCNV) as a helper virus to study the genes
involved in abiotic stress responses in tomato (He et al., 2008;
Guo et al., 2010). DNAβ satellite virus is devoid of the undesired
effects of virus infection and instead functions to deliver the target
gene fragment. RNA virus based VIGS systems with satellite and
helper RNAs have also been developed. Here the satellite virus
vector helps to deliver RNA into plants and the helper viruses
supply replication and movement proteins. The advantage of twocomponent system is, it produces stronger silencing phenotypes
compared to the satellite viruses alone (Gosselé et al., 2002).
In contrast to dicotyledonous plants, monocotyledonous
plants have only a few VIGS vectors to date (Scofield and Nelson,
2009; Hema et al., 2013). Among these, the Barley stripe mosaic
virus (BSMV)-based vector is the most widely used VIGS vector
for functional analysis of abiotic stress genes in wheat (Triticum
aestivum) (Kuzuoglu-Ozturk et al., 2012; Kang et al., 2013;
Manmathan et al., 2013) and barley (Hordeum vulgare) (Liang
et al., 2012). The availability of other vector resources and the
potential of VIGS in monocotyledonous species have been comprehensively reviewed recently (Scofield and Nelson, 2009; Hema
et al., 2013).

RECENT IMPROVEMENTS IN VIGS
Apart from a number of new VIGS vectors developed to suit
a wide range of crop species, existing VIGS vectors and the
technique have undergone several improvements in the recent
past. For example, viral vectors have been modified to improve
silencing efficiency. Recently, the RNA1 component of the bipartite TRV-vector was modified to serve as a VIGS vector which
can infect plants systemically in the absence of RNA2 (Deng
et al., 2013). This vector was developed by partially removing
the 16K cysteine rich protein. The advantage of 16K protein
removal is that it creates space for target gene cloning which
otherwise cloned in RNA2 and also reduces the silencing suppression capacity of TRV. Furthermore, attempts have been made to
identify gene-silenced tissues through a VIGS vector. For example, a GREEN FLUORESCENT PROTEIN (GFP) gene has been
tagged to the coat protein gene of TRV2 for easy identification
of silenced tissue (Tian et al., 2014). This will help in tracing only green fluorescent tissues that have the virus, which are

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expected to have silencing, and hence facilitate the use of these
tissues for abiotic stress assays. Some VIGS vectors have also been
used to induce transcriptional gene silencing (TGS). Cloning of
endogenous target gene promoter into viral vector and delivery
into plants results in the production of siRNAs homologous to
the endogenous gene promoter. These siRNAs facilitate RNAdirected DNA methylation (RdDM) and histone modifications,
resulting in RNA-mediated gene silencing (Kanazawa et al., 2011).
This can help suppress the regulators of abiotic stress response.
In addition to improvements in VIGS vectors, VIGS procedure
has been modified to perform silencing in different tissues. Gene
silencing has been demonstrated in detached plant parts like
petals (Dai et al., 2012), leaves and fruits (Romero et al., 2011;
Ramegowda et al., 2013). This will facilitate high-throughput
silencing and multiple stress impositions. VIGS has also been
used to silence genes during tissue culture and callus development
(Anand et al., 2007) which can facilitate precise stress imposition
and high-throughput screening.

VIGS FOR STUDYING ABIOTIC STRESS RESPONSES IN CROP
SPECIES
VIGS has been used to investigate gene functions under abiotic
stresses in model species. These studies involving model plants
(Ahn et al., 2006; Moeder et al., 2007; Qian et al., 2007; SenthilKumar et al., 2007; Ahn and Pai, 2008; Cho et al., 2008; Hong
et al., 2008; Sarowar et al., 2008; Govind et al., 2009; Ré et al.,
2011) are not discussed in this review; instead, the main focus
is given to studies involving crop plants. Recently, development
of a wide range of VIGS vectors with high silencing efficiency
has expanded the application of VIGS to several crop species for
studying abiotic-stress-responsive genes (Table 1). The following sections enumerate the studies in which VIGS was used to
characterize abiotic-stress-responsive genes in crop plants.
DROUGHT STRESS TOLERANCE

VIGS is a valuable tool for functional validation of droughtresponsive genes identified from transcript profiling of plants
exposed to drought stress. TRV-VIGS-mediated silencing of lea4,
a gene encoding late embryogenesis abundant protein (LEA),
resulted in increased susceptibility of tomato plants to drought
stress. This gene was identified from a subtracted cDNA library
for drought-stress-responsive genes (Gopalakrishna et al., 2001).
At a given drought stress level, lea4-silenced plants wilted faster
and recovered slower upon re-watering than the wild-type and
vector control plants. lea4-silenced plants also exhibited reduced
osmotic adjustment, reduced cell viability and higher superoxide
radical levels (Senthil-Kumar and Udayakumar, 2006). In another
study, a GLUTAREDOXIN gene, SlGRX1, was shown to regulate
the drought stress response in tomato using a satellite-virus-based
vector, DNAmβ (Guo et al., 2010). Under drought stress, silenced
plants showed decreased chlorophyll content and decreased relative water content (RWC) compared to vector control plants
(Guo et al., 2010). To study the role of mitogen-activated protein kinases (MAPKs) in drought tolerance of S. pimpinellifolium, a wild species of tomato, SpMPK1, SpMPK2, and SpMPK3
genes were silenced individually or together using TRV-VIGS.
Results suggested that co-silencing of SpMPK1/SpMPK2 impaired

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VIGS for abiotic stress studies

ABA- and H2 O2 -induced stomatal closure and enhanced ABAinduced H2 O2 production. But this response was not seen
when SpMPK1 and SpMPK2 were silenced individually, suggesting these two genes are functionally redundant. This indicates
that VIGS can be used to study functionally redundant genes.
Reduced drought tolerance was also seen in SpMPK3 alone and
SpMPK1/SpMPK2/SpMPK3 co-silenced plants (Li et al., 2013).
Similarly, silencing of the SlMPK4 gene in tomato resulted
in early wilting and reduced tolerance of plants to drought
stress (Virk et al., 2013). TRV-VIGS-mediated silencing of extracellular PEROXIDASE 2 (CaPO2) in chili pepper resulted in
increased susceptibility of silenced plants to mannitol-induced
osmotic stress. Leaf disks from CaPO2-silenced leaves showed
severe bleaching and higher chlorophyll loss than vector control plants (Choi and Hwang, 2012). Similarly, silencing of the
ABI3/VP1 transcription factor (CaRAV1) alone or together with
OXIDOREDUCTASE (CaOXR1), using the TRV-VIGS vector,
conferred reduced tolerance to mannitol-induced osmotic stress
compared to vector control plants (Lee et al., 2010). This was
accompanied by reduced expression of the known drought-stressresponsive genes ANTIMICROBIAL PROTEIN (CaAMP1) and
OSMOTIN (CaOSM1) (Hong et al., 2004; Lee and Hwang, 2009).
A recent study (Lim and Lee, 2014) implicated the involvement
of MILDEW RESISTANCE LOCUS O (CaMLO2) in drought tolerance in chili pepper. Silencing of CaMLO2 using the TRV-VIGS
vector in chili pepper plants showed lower levels of transpirational
water loss and lipid peroxidation in dehydrated leaves compared
to wild-type plants. This study showed that CaMLO2 acts as a
negative regulator under drought stress conditions.
Another study demonstrated the usefulness of the TRVbased VIGS technique to study dehydration-responsive genes in
rose flowers. Individual silencing of the NAC TRANSCRIPTION
FACTOR 2 (RhNAC2) and A-TYPE EXPANSIN 4 (RhEXPA4)
in rose petals and petal disks reduced the recovery of petals
and petal disks during rehydration (Dai et al., 2012). Similarly,
silencing of NAC TRANSCRIPTION FACTOR 3 (RhNAC3) in
rose petals has resulted in a decrease in cell expansion of
the petals during rehydration along with concomitant downregulation of several stress- and cell-expansion-related genes in
the silenced petals compared to the vector control (Jiang et al.,
2014). These genes are possible candidates for improving the
shelf life of rose flowers through reduced water loss. Silencing
of the ACC SYNTHASE 1 (RhACS1) and ACC SYNTHASE 2
(RhACS2) genes individually or co-silencing of both genes suppressed dehydration- and rehydration-induced ethylene in the
sepals and gynoecia. Reduced ethylene production resulted in
improved petal cell expansion during dehydration. On the contrary, silencing of an ethylene receptor, RhETR3, enhanced the
inhibitory effect of dehydration on petal cell expansion (Liu et al.,
2013). These results suggest that ethylene mediates dehydrationinduced inhibition of cell expansion in rose petals.
VIGS has also been used to study drought stress response in
monocotyledonous crop species. In a recent study (Manmathan
et al., 2013), two drought-stress-responsive genes, ENHANCED
RESPONSE TO ABSCISIC ACID (Era1) and INOSITOL
POLYPHOSPHATE 1-PHOSPHATASE (Sal1), were individually
silenced in wheat using the BSMV-VIGS vector. Era1 gene

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VIGS for abiotic stress studies

Table 1 | List of abiotic-stress-related genes silenced in crop plants using VIGS.
VIGS
vector

Crop
species

Silenced target gene

Abiotic stress

Changes in gene-silenced
plants exposed to stress
(compared to vector control
plants)

References

BSMV

Wheat

TaEra1 (ENHANCED RESPONSE TO
ABSCISIC ACID), TaSal1 (INOSITOL
POLYPHOSPHATE 1-PHOSPHATASE)

Drought

Increased relative water content
(RWC), increased water use
efficiency (WUE), reduced
stomatal conductance, reduced
transpiration rate and higher
plant vigor

Manmathan et al.,
2013

TaBTF3 (BASIC TRANSCRIPTION
FACTOR 3)

Drought

Wilted and curled leaves under
severe drought, higher water
loss rate (WLR), decreased
RWC and survival rate, lower
free proline content, and
increased membrane leakage

Kang et al., 2013

TaPGR5 (PROTON GRADIENT
REGULATION 5)

High light-induced
photo-inhibition

Inhibition of photosynthesis,
reduced non-photochemical
quenching, increased
membrane damage,
anthocyanin and
malondialdehyde (MDA)
accumulation

Yuan-Ge et al., 2014

Wild
emmer
wheat

TdAtg8 (AUTOPHAGY-RELATED 8)

Drought

Decreased chlorophyll content
and increased MDA

Kuzuoglu-Ozturk
et al., 2012

Barley

HvHVA1 (H. VULGARIS ABUNDANT
PROTEIN)

Drought

Higher WLR in detached leaves,
less survival, and retarded
growth with reduced height and
less total dry weight

Liang et al., 2012

HvDhn6 (DEHYDRIN)

Drought

Less survival, retarded growth
and reduced total dry weight

Liang et al., 2012

BPMV

Soybean

GmRPA3 (REPLICATION PROTEIN A)

Iron deficiency

Reduced chlorosis, increased
chlorophyll, stunting and shorter
internode

Atwood et al., 2014

PEBV

Pea

PsSym19 (SYMBIOTIC)

Arbuscular- mycorrhizalsymbiosis-associated Pi
uptake

Less development of arbuscules
and vesicles in the root cortex
of silenced plants

Grønlund et al., 2010

PsPT4 (PUTATIVE PI TRANSPORTER)

Arbuscular-mycorrhizalsymbiosis-associated Pi
uptake

Reduced phosphate uptake in
new roots

Grønlund et al., 2010

TRX-F, TRX-M (THIOREDOXIN)

Oxidative stress

Pale-green phenotype,
reduction in the following: Mg
chelatase activity,
5-aminolevulinic acid synthesis,
chlorophyll, carotenoid pigment,
photosynthesis and expression
of tetrapyrrole biosynthesis
pathway genes and increased
accumulation of ROS

Luo et al., 2012

(Continued)

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VIGS for abiotic stress studies

Table 1 | Continued
VIGS
vector

Crop
species

Silenced target gene

Abiotic stress

Changes in gene-silenced
plants exposed to stress
(compared to vector control
plants)

References

TRV

Tomato

Sllea4 (LATE EMBRYOGENESIS
ABUNDANT PROTEIN 4)

Drought or oxidative
stress

Leaf wilting, reduced osmotic
adjustment and cell viability,
accumulation of higher
superoxide radicals

Senthil-Kumar and
Udayakumar, 2006

SpMPK1 (MITOGEN-ACTIVATED
PROTEIN KINASE 1), SpMPK2
(MITOGEN-ACTIVATED PROTEIN
KINASE 2), SpMPK3
(MITOGEN-ACTIVATED PROTEIN
KINASE 3)

Drought or ABA or
oxidative stress

Reduced survival, higher water
loss in detached leaves,
increased stomatal closure in
response to ABA and increased
H2 O2 production in presence of
ABA

Li et al., 2013

SlMPK4 (MITOGEN-ACTIVATED
PROTEIN KINASE 4)

Drought

Early leaf wilting

Virk et al., 2013

CaPO2 (PEROXIDASE 2)

Salt or osmotic stress

Reduced chlorophyll content
and increased lipid peroxidation

Choi and Hwang,
2012

CaRAV1 (RELATED TO ABI3/VP1),
CaOXR1 (OXIDOREDUCTASE 1)

Salt or osmotic stress

Severe bleaching of leaf discs,
loss of chlorophyll and increased
lipid peroxidation

Lee et al., 2010

CaMLO2 (MILDEW RESISTANCE
LOCUS O)

Drought

Less water loss and lipid
peroxidation

Lim and Lee, 2014

RhNAC2 (NAC TRANSCRIPTION
FACTOR 2), RhEXPA4 (A-TYPE
EXPANSIN 4)

Dehydration

Reduced fresh weight, petal
width and recovery from
dehydration

Dai et al., 2012

RhNAC3 (NAC TRANSCRIPTION
FACTOR 3)

Dehydration

Reduced cell expansion during
recovery

Jiang et al., 2014

RhACS1 (ACC SYNTHASE 1), RhACS2
(ACC SYNTHASE 2)

Dehydration

Reduced ethylene production
and cell density decreased

Liu et al., 2013

RhETR3 (ETHYLENE RECEPTOR)

Dehydration

Inhibition of petal expansion and
cell expansion

Liu et al., 2013

SlGRX1 (GLUTAREDOXIN 1)

Oxidative or drought or
salt stress

Reduced chlorophyll, leaf
wilting, curled leaves and
reduced RWC under drought;
no further growth with wilted
leaves and reduced chlorophyll
under salt stress

Guo et al., 2010

SlFRO1 (FERRIC CHELATE
REDUCTASE 1)

Nutrient deficiency

Reduced ferric chelate
reductase activity in roots

He et al., 2008

Chili
pepper

Rose

TYLCCNV

Tomato

encodes the β-subunit of farnesyltransferase involved in ABA
mediated stomatal closure by activating the guard cell S-type
anion-channels and increasing the cytosolic Ca2+ concentration. The loss-of-function of Era1 has been shown to enhance
ABA sensitivity and hence reduced stomatal conductance and
water loss (Cutler et al., 1996; Allen et al., 2002; Wang et al.,
2005). Similarly, Sal1 has been shown to act as a negative
regulator of both ABA-independent and ABA-dependent stress
response pathways. Its loss-of-function has shown to increase

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the sensitivity of plants to drought stress (Wilson et al., 2009).
Era1- and Sal1-silenced plants subjected to drought stress showed
increased RWC, improved water use efficiency (WUE) and
better vigor compared to vector-inoculated plants. This suggests
that down-regulation of Era1 and Sal1 genes enhances drought
tolerance in wheat by decreasing sensitivity to ABA. In another
study, H. VULGARIS ABUNDANT PROTEIN (HvHVA1) and
DEHYDRIN 6 (HvDhn6), genes encoding the LEA class of proteins, were individually silenced in wheat using the BSMV-based

July 2014 | Volume 5 | Article 323 | 66

Ramegowda et al.

VIGS vector (Liang et al., 2012). Under drought stress, both
HVA1- and Dhn6-silenced plants showed lower survival rates
than vector control plants. In addition, HVA1-silenced plants
showed a higher rate of water loss under drought stress compared
to vector control plants. However, the silenced plants also
showed reduced vegetative growth and lower biomass even under
well-watered conditions. This suggested the involvement of
HvHVA1 and HvDhn6 in growth and development apart from
drought tolerance (Liang et al., 2012). BSMV-VIGS-mediated
silencing of the BASIC TRANSCRIPTION FACTOR 3 (TaBTF3)
gene in wheat resulted in a decreased plant survival rate, less
free proline content, less RWC and increased membrane leakage
compared to vector control plants under drought stress (Kang
et al., 2013). Similarly, BSMV-VIGS-mediated silencing of
AUTOPHAGY-RELATED 8 (TdAtg8) from Triticum dicoccoides
(wild emmer wheat) resulted in reduced chlorophyll content
and an increase in malondialdehyde (MDA) content in silenced
plants under drought stress (Kuzuoglu-Ozturk et al., 2012). The
increased levels of MDA indicate membrane damage due to
lipid peroxidation mainly by the effect of reactive oxygen species
(ROS) (Zhang and Kirkham, 1994).
Taken together, these studies demonstrate the versatility of
VIGS in deciphering the role of drought-stress-responsive genes
in both dicotyledonous and monocotyledonous plants. In addition, the application of VIGS in silencing drought-stress-related
genes in flowers (Dai et al., 2012) signifies its efficacy in studying the reproductive-tissue-associated genes which are important during terminal drought stress. Furthermore, VIGS has the
potential to identify negative regulators of drought stress response
during the reproductive stage.
SALT-STRESS TOLERANCE

The utility of VIGS in investigating salt stress tolerance in crop
plants has also been demonstrated. SlGRX1 gene silencing in
tomato by a satellite DNAmβ-based VIGS vector resulted in yellowing of leaves under salinity stress compared to vector control
plants due to a reduction in chlorophyll content, suggesting the
role of GRX1 in salt tolerance (Guo et al., 2010). Further, the
role of CaRAV1 and CaOXR1 has been studied by TRV-VIGS
in chili pepper (Lee et al., 2010). Leaf disks from CaRAV1-only
silenced and CaRAV1/CaOXR1 co-silenced plants exposed to different concentrations of NaCl showed severe bleaching due to
loss of chlorophyll compared to vector control plants. Similarly,
TRV-VIGS-mediated silencing of CaPO2 resulted in a reduction in chlorophyll content and higher lipid peroxidation, leading
to increased susceptibility of silenced chili pepper plants to salt
stress compared to vector control plants (Choi and Hwang, 2012).
Consistently, ectopic expression of CaPO2 in Arabidopsis conferred enhanced tolerance to high salt stress, suggesting the role
of CaPO2 in salinity tolerance (Choi and Hwang, 2012). Taken
together, these studies demonstrate the usefulness of VIGS in
functional analysis of genes involved in salinity tolerance in crop
plants.
OXIDATIVE STRESS TOLERANCE

ROS increases in plants challenged by drought, salinity, extreme
temperatures, or high light stress (Pastori and Foyer, 2002); this

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VIGS for abiotic stress studies

in turn leads to oxidative stress (Apel and Hirt, 2004). VIGS has
been used to study oxidative stress tolerance in the recent past.
A few studies (Lee et al., 2010; Choi and Hwang, 2012) described
earlier in this review that examined the role of chili pepper genes,
like CaRAV1, CaOXR1, and CaPO2, have also described oxidative
stress damage in the plants with these genes silenced. Silencing
of CaRAV1, CaOXR1, or CaPO2 individually, or co-silencing of
CaRAV1/CaOXR1 in chili pepper resulted in enhanced lipid peroxidation under stress (Lee et al., 2010; Choi and Hwang, 2012).
Similarly, downregulation of CaMLO2 expression in chili pepper using TRV-based VIGS resulted in lower MDA levels under
drought stress compared to vector control plants (Lim and Lee,
2014). This indicated the plausible negative role of CaMLO2
under drought as well as oxidative stress. In wheat, silencing of
TdAtg8 using BSMV-based VIGS resulted in higher MDA levels
compared to vector control under drought stress, thus suggesting the possible involvement of TdAtg8 under oxidative stress
(Kuzuoglu-Ozturk et al., 2012). High light stress induces oxidative stress in chloroplast. A recent study (Yuan-Ge et al., 2014)
used BSMV-based VIGS to silence the PROTON GRADIENT
REGULATION 5 (TaPGR5) gene in wheat to test its involvement in tolerance to photo-inhibition under high light treatment. High light inhibited the net photosynthesis and affected
the maximal quantum yield of Photosystem II (Fv/Fm) in the
silenced plants. Also, silenced plants showed increased membrane
damage, anthocyanin accumulation and higher MDA, suggesting the role of TaPGR5 in oxidative stress tolerance. In pea,
PEBV-VIGS-mediated co-silencing of thioredoxin genes, TRXF/TRX-M, resulted in a significant reduction in Mg-chelatase
activity and 5-aminolevulinic acid synthesizing capacity. This
was associated with reduced chlorophyll and carotenoid pigment
contents, lowered photosynthetic capacity and reduced expression of tetrapyrrole biosynthesis pathway genes, leading to the
accumulation of ROS (Luo et al., 2012). Altogether, these studies highlight the utility of VIGS in characterizing the genes that
mitigate oxidative stress in crop plants.

VIGS FOR FUNCTIONAL ANALYSIS OF MINERAL
NUTRITION-RELATED GENES IN CROP PLANTS
Differential expression of a large number of genes in response to
nutrient deficiency or toxicity has been shown in plants (Wang
et al., 2002; Becher et al., 2004; Hirai et al., 2004; Takehisa
et al., 2013), but only a few of them have been functionally
characterized. In a soybean (Glycine max) iron-inefficient line,
Isoclark, a Bean pod mottle virus (BPMV)-based VIGS vector was
used to silence a REPLICATION PROTEIN A (GmRPA3) gene.
GmRPA3-silenced plants had smaller leaves, decreased internode
length and higher chlorophyll content, and failed to respond to
increased iron nutrition, suggesting a role of the GmRPA3 gene
in iron acquisition (Atwood et al., 2014). Using a satellite DNA
(DNAmβ) virus system with TYLCCNV, the function of FERRIC
CHELATE REDUCTASE gene (FRO1) was studied in tomato
roots (He et al., 2008). Silencing of FRO1 resulted in reduced ferric chelate reductase activity in roots. In pea (Pisum sativum),
a Pea early browning virus (PEBV)-based vector was used to
study arbuscular-mycorrhizal-fungi (AMF)-associated phosphate
acquisition. Silencing of a symbiotic gene, PsSym19, reduced the

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VIGS for abiotic stress studies

development of both arbuscules and vesicles at the root cortex. Similarly, silencing of a putative Pi transporter gene, PsPT4,
using the PEBV-vector, reduced the phosphate uptake (Grønlund
et al., 2010), suggesting the importance of these genes in phosphate assimilation in pea plants. Taken together, these studies
suggest that VIGS can be effectively used to analyze gene function
associated with nutrient deficiency in crop plants.

a high-throughput manner (Liu et al., 2002b). Each Agro-clone
is inoculated into individual plants using a feasible inoculation
method. The Agro-clones which produce interesting phenotype
under abiotic stress can be quickly identified and sequenced to
identify the inserted gene (Supplementary Figure 4). In addition to several general advantages, VIGS has some advantages
pertinent to characterizing abiotic-stress-responsive genes.

ADVANTAGES OF USING VIGS TO STUDY ABIOTIC STRESS
TOLERANCE IN CROP PLANTS

LIMITATIONS OF VIGS IN STUDYING ABIOTIC STRESS
TOLERANCE MECHANISMS AND SOLUTIONS TO
OVERCOME THE LIMITATIONS

VIGS has several advantages over most established functional
genomics tools (Burch-Smith et al., 2004; Purkayastha and
Dasgupta, 2009; Unver and Budak, 2009; Stratmann and Hind,
2011; Pflieger et al., 2013). (1) VIGS is faster and relatively easy
to perform. VIGS can produce loss-of-function phenotype of
a specific gene in a short period resulting in rapid functional
characterization of genes (Dinesh-Kumar et al., 2003). (2) VIGS
avoids plant transformation. Functional characterization of genes
in difficult to transform species would be more easier once the
VIGS system is established in that species (Burch-Smith et al.,
2004). (3) VIGS allows functional analysis of genes whose lossof-function produces lethal phenotype. It can be used to study
genes related to embryonic development and seedling emergence
and vigor (an important abiotic stress tolerance trait) (Ratcliff
et al., 2001; Burch-Smith et al., 2004; Liu et al., 2004). (4) VIGS
can overcome functional redundancy. Using the most conserved
regions in VIGS, the multiple related genes or gene families can
be silenced together (Ekengren et al., 2003; He et al., 2004). By
silencing two or more members of the gene family with redundant
functions the complex signaling components associated abiotic
stresses such as drought can be deciphered. Though other functional genomics tools like antisense RNAs, artificial miRNAs, or
RNAi can also be used for this purpose, but they are time consuming. (5) VIGS enables timely silencing of tissue-specific genes.
For example, plants being infected only at the time of flowering
or panicle development will predominantly have genes silenced
in that organ. Besides, VIGS can be used to quickly silence genes
in a particular gene mutant, stable RNAi or gene-overexpression
plants. This will enable studying gene interactions under complex abiotic stresses in a large-scale and shorter time. In addition,
VIGS is a feasible functional genomics tool over other PTGSmediated gene silencing methods (Supplementary Table 3). VIGS
is versatile, which allows rapid comparisons of gene function
between species and works in different genetic backgrounds
where genetic transformation is tedious and time consuming.
VIGS also serves as a high-throughput forward as well as reverse
genetics tool in plants. VIGS as a high-throughput reverse genetics tool can be performed by individually cloning fragments
(usually 300–500 base pairs) from a large number of target genes
into a suitable viral vector. The viral vector is delivered into plants
using different methods. Abiotic stress can be applied 2–3 weeks
after inoculation and the loss-of-function phenotype can be studied in the silenced plants to attribute function for the target gene
under abiotic stress (Supplementary Figure 3). Similarly, VIGS
as a forward genetics tool enables identification of critical players in stress tolerance. The stress specific cDNA pool can be
cloned into binary vectors and transformed into A. tumefaciens in

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Though VIGS has been proved to be a robust tool for functional
genomics studies, it has several limitations. These limitations and
ways to overcome the same are listed below. (1) The virus vector
may accumulate to high levels in the silenced plant if the silenced
target gene is involved in the immunity of plants against the virus
and such plants can become highly susceptible to subsequent
abiotic stress. This will adversely influence studying the specific
effect of gene silencing on abiotic stress tolerance. Quantification
of viral load (Senthil-Kumar and Mysore, 2011b) in the silenced
plants helps to decide whether the virus has accumulated higher
than in the non-silenced control plant and this information can
be used to choose different region of the target gene for silencing. (2) Virus infection by itself can interfere with abiotic stress
response. For example, infection of Brome mosaic virus (BMV),
Cucumber mosaic virus (CMV), Tobacco mosaic virus (TMV) and
TRV delayed the appearance of drought symptoms in various
plant species (Xu et al., 2008). The VIGS vector along with abiotic stress can create a scenario like concurrent biotic and abiotic
stress. The phenotype produced under this situation might be different from abiotic stress alone (Suzuki et al., 2014). This can
be overcome by including appropriate non-silenced vector control plants and comparing the results with specific gene silenced
plants. (3) Silencing can be affected by changes in environmental
conditions during abiotic stress treatment. Temperature, relative
humidity and light can influence silencing (Fu et al., 2005, 2006;
Kotakis et al., 2010). VIGS efficiency is reduced under high temperatures due to reduced virus multiplication (Chellappan et al.,
2005). This can be overcome by verifying the viral multiplication
beforehand and maintaining the VIGS vector-inoculated plants
under optimum environmental conditions until the silencing followed by abiotic stress imposition. Ways to overcome some of
the limitations of VIGS to study abiotic-stress-associated genes
are also described in our earlier review (Senthil-Kumar and
Udayakumar, 2010).

CONCLUSION AND FUTURE PROSPECTS
VIGS, as both a forward and reverse genetics tool, offers opportunities for rapid functional analysis of abiotic-stress-related genes
in both dicotyledonous and monocotyledonous crop species.
Utilization of VIGS for understanding the mechanisms of abiotic
stress tolerance and crop improvement is depicted in Figure 1.
Currently, nearly 50 plant species have been shown to be
amenable for VIGS (Lange et al., 2013), and VIGS is expected to
be expanded to many other crop plants in future. Stress imposition protocols for VIGS plants have been optimized for several
abiotic stresses, including drought, salinity and oxidative stress,

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Ramegowda et al.

FIGURE 1 | Model showing the application of VIGS in
understanding the mechanisms of abiotic stress tolerance and
crop improvement. VIGS can be used as a powerful reverse
genetic tool for functional analysis of abiotic-stress-responsive genes
identified from cultivars, land races and their wild relatives though
transcriptome analysis and comparative analysis of molecular marker,
proteome and metabolite data. VIGS can also be used for a
high-throughput forward genetics screening. This is achieved by
cloning the cDNA libraries generated from abiotic-stressed plants
directly into a VIGS vector, inoculating them on target plants and
analyzing the knockdown plants under abiotic stress. Along with
target-gene-silenced plants, vector control and visible marker gene
(like phytoene desaturase, PDS or magnesium protoporphyrin chelatase

Frontiers in Plant Science | Plant Genetics and Genomics

VIGS for abiotic stress studies

subunit H, ChlH)-silenced plants showing a photo-bleaching/yellowing
phenotype will aid in identifying the time of initiation and duration
of gene silencing. Silencing of a gene known to be involved in the
specific abiotic stress tolerance that leads to susceptibility under
stress (positive controls) is useful for coinciding abiotic stress
imposition at the time of target gene silencing. In addition,
high-throughput stress imposition and stress effect quantification
methods can be used to screen large numbers of gene-silenced
plants (Ramegowda et al., 2013). Candidate genes identified from the
screen can be further confirmed by generating stable RNAi or
overexpression transgenic lines. The trait can then be transferred to
elite cultivars through breeding or generating transgenics in amenable
cultivars to develop stress-tolerant crop plants.

July 2014 | Volume 5 | Article 323 | 69

Ramegowda et al.

and extreme temperatures (Ramegowda et al., 2013). Recently, a
modified virus vector has been developed to express artificial and
endogenous miRNAs in plants (Tang et al., 2010). Virus-vectormediated silencing using artificial miRNA will be useful for
functional analysis of abiotic-stress-associated miRNAs in crop
plants. This approach will combine the specificity of amiRNA
and versatility of VIGS. VIGS could also assist plant breeding
programs in validating quantitative trait loci (QTL) and genes
associated with abiotic stress traits (Cheng et al., 2010). Most of
the QTL identified by molecular marker technologies would have
multiple candidate genes. VIGS could serve as an effective and
robust functional genomics tool to validate each gene in the locus.
For example, a combination of cDNA-amplified fragment length
polymorphism (AFLP) and VIGS can be used to screen a large
number of genes and identify genes associated with abiotic stress
tolerance. In summary, VIGS can play a major role in understanding abiotic stress tolerance mechanisms. This will have a direct
impact on developing crop varieties that are tolerant to abiotic
stress.

AUTHOR CONTRIBUTIONS
Venkategowda Ramegowda and Muthappa Senthil-Kumar
wrote the manuscript, and Kirankumar S. Mysore edited the
manuscript.

ACKNOWLEDGMENTS
VIGS-based projects at Muthappa Senthil-Kumar’s laboratory are
supported by core funding from the National Institute of Plant
Genome Research and at Kirankumar S. Mysore’s laboratory
by The Samuel Roberts Noble Foundation. Authors thank Mr.
Mehanathan Muthamilarasan and Dr. Aiswarya Baruah for critical reading of the manuscript and Ms. Jackie Kelley for help with
editing the manuscript.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online
at: http://www.frontiersin.org/journal/10.3389/fpls.2014.00323/
abstract

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.

Frontiers in Plant Science | Plant Genetics and Genomics

VIGS for abiotic stress studies

Received: 12 February 2014; accepted: 19 June 2014; published online: 08 July 2014.
Citation: Ramegowda V, Mysore KS and Senthil-Kumar M (2014) Virus-induced
gene silencing is a versatile tool for unraveling the functional relevance of multiple
abiotic-stress-responsive genes in crop plants. Front. Plant Sci. 5:323. doi: 10.3389/
fpls.2014.00323
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Ramegowda, Mysore and Senthil-Kumar. This is an openaccess article distributed under the terms of the Creative Commons Attribution
License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original
publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with
these terms.

July 2014 | Volume 5 | Article 323 | 73

ORIGINAL RESEARCH ARTICLE
published: 14 May 2014
doi: 10.3389/fpls.2014.00187

Comparative phylogenomics of the CBL-CIPK
calcium-decoding network in the moss Physcomitrella,
Arabidopsis, and other green lineages
Thomas J. Kleist 1*, Andrew L. Spencley 1,2 and Sheng Luan 1*
1
2

Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
Department of Dermatology, Stanford University, Stanford, CA, USA

Edited by:
Rohini Garg, National Institute of
Plant Genome Research, India
Reviewed by:
Caroline Gutjahr, Ludwig Maximilian
University of Munich, Germany
Matthew R. Willmann, University of
Pennsylvania, USA
*Correspondence:
Thomas J. Kleist and Sheng Luan,
451 Koshland Hall Berkeley,
CA 94720, USA
e-mail: kleist@berkeley.edu;
sluan@berkeley.edu

Land plants have evolved a host of anatomical and molecular adaptations for terrestrial
growth. Many of these adaptations are believed to be elaborations of features that were
present in their algal-like progenitors. In the model plant Arabidopsis, 10 Calcineurin
B-Like proteins (CBLs) function as calcium sensors and modulate the activity of 26
CBL-Interacting Protein Kinases (CIPKs). The CBL-CIPK network coordinates environmental
responses and helps maintain proper ion balances, especially during abiotic stress.
We identified and analyzed CBL and CIPK homologs in green lineages, including CBLs
and CIPKs from charophyte green algae, the closest living relatives of land plants.
Phylogenomic evidence suggests that the network expanded from a small module, likely
a single CBL-CIPK pair, present in the ancestor of modern plants and algae. Extreme
conservation of the NAF motif, which mediates CBL-CIPK physical interactions, among
all identified CIPKs supports the interpretation of CBL and CIPK homologs in green algae
and early diverging land plants as functionally linked network components. We identified
the full complement of CBL and CIPK loci in the genome of Physcomitrella, a model
moss. These analyses demonstrate the strong effects of a recent moss whole genome
duplication: CBL and CIPK loci appear in cognate pairs, some of which appear to be
pseudogenes, with high sequence similarity. We cloned all full-length transcripts from
these loci and performed yeast two-hybrid analyses to demonstrate CBL-CIPK interactions
and identify specific connections within the network. Using phylogenomics, we have
identified three ancient types of CBLs that are discernible by N-terminal localization
motifs and a “green algal-type” clade of CIPKs with members from Physcomitrella and
Arabidopsis.
Keywords: CBL-CIPK, calcium signaling, plant abiotic stress physiology, plant nutrition, evolution, molecular

INTRODUCTION
Of the events that have shaped our modern biosphere, the colonization of land by the predecessors of modern embryophytes
stands out as an evolutionary advent that has profoundly affected
our landscape and terrestrial ecology. Land plants arose roughly
450 million years ago from a lineage of multicellular freshwater green algae known as charophytes (Graham, 1996; Lewis and
McCourt, 2004). Land plants have elaborated and expanded upon
a molecular toolkit present in their charophyte ancestors and
thereby developed novel anatomical and molecular adaptations
to withstand life on land (Graham, 1996; Kenrick and Crane,
1997; Pittermann, 2010; Timme and Delwiche, 2010). The switch
from aquatic to terrestrial growth imposed new and formidable
abiotic stresses. Discontinuous access to water combined with
labile, often unfavorable ion balances spurred the development
of sophisticated mechanisms for the perception of water and ion
availability, the communication of this information throughout
the plant body, and the coordination of orchestrated responses to
these stresses.

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Calcium ions play a pivotal role in a host of signal transduction cascades in plants as well as in animals. Tightly localized
spikes in cytosolic calcium concentration in response to particular environmental cues have been extensively documented in
plant cells and are thought to act as early steps in plant signaling pathways (Gilroy et al., 1993; Evans et al., 2001). These bursts,
known as calcium signals, are modulated by channels that allow
calcium entry from both outside the cell and inside cellular stores
(e.g., the vacuole, endoplasmic reticulum). Calcium signals are
decoded by proteins that act as sensors; calcium sensors often
contain helix-loop-helix motifs known as EF hands that bind calcium and induce conformational changes to modulate the activity
of other proteins or domains (Hrabak et al., 2003; McCormack
et al., 2005).
Calcineurin B-Like proteins or CBLs are a family of calcium
sensors found in all studied land plants and some chlorophyte
green algae (Weinl and Kudla, 2009; Batistic et al., 2011). CBLs
are named based on their homology to the B regulatory subunit of the phosphatase calcineurin (Luan et al., 2002). CBLs

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contain four calcium-binding EF hands and typically contain
a subcellular localization signal at their N-terminus. The most
thoroughly characterized CBLs to date contain a dual lipid modification motif (MGCXXS/T) at their N-terminus that is necessary
and sufficient for targeting of fluorescent protein (FP)-fusions to
the plasma membrane (Batistic et al., 2008, 2010). Other CBLs
are reported to localize to the vacuole, and several of these CBLs
contain a distinct N-terminal extension known as the Tonoplast
Targeting Sequence (TTS) that targets FP-fusions to the tonoplast
(Batistič, 2012; Tang et al., 2012). Uniquely, Arabidopsis CBL10
contains a putative N-terminal transmembrane helix that anchors
it to the tonoplast (Kim et al., 2007; Batistic et al., 2010) or plasma
membrane (Quan et al., 2007; Ren et al., 2013). Subcellular targeting has been shown to be critical for CBL functionality, and CBLs
are responsible for the recruitment and localization of protein
partners.
CBLs physically and functionally interact with CBLInteracting Protein Kinases (CIPKs) and modulate their
kinase activity (Shi et al., 1999; Batistic et al., 2011). Hence, the
CBL-CIPK network serves to decode calcium signals and transmit
these signals through reversible protein phosphorylation. CIPKs,
also known as SnRK3 proteins, are serine/threonine protein
kinases that consist of a N-terminal kinase domain similar
to those found in other plant protein kinases and a unique
C-terminal regulatory domain that acts as an autoinhibitory
domain and mediates interactions with CBLs. CBLs bind to a
short, conserved region within the C-terminal autoinhibitory
domain of CIPKs known as the NAF or FISL motif (Shi et al.,
1999; Albrecht et al., 2001; Guo et al., 2001). In addition to modulating the kinase activity of CIPKs, CBLs are thought to be the
sole or primary determinants of CBL-CIPK complex localization,
therefore they are thought to act as functional modules (Luan,
2009; Batistic et al., 2011). CBLs are believed to recruit CIPKs,
which lack any sort of discernible targeting signals, to these
surfaces, possibly in a calcium-dependent manner (Batistic̆ and
Kudla, 2009; Batistic et al., 2010).
Initial functional analysis of the CBL-CIPK network came
from the genetic identification of the Salt Overly Sensitive (SOS)
pathway. Together, CBL4/SOS3 and CIPK24/SOS2 modulate that
activity of the plasma membrane Na+ /H+ exchanger SOS1.
Mutants lacking any component of the Salt Overly Sensitive
(SOS) pathway display NaCl-hypersensitive phenotypes (Liu and
Zhu, 1998; Liu et al., 2000; Shi et al., 2000). CBL4/SOS3 and
CIPK24/SOS2 belong to large proteins families containing 10
CBLs and 26 CIPKs in Arabidopsis and similarly sized families in
other angiosperms (Kudla et al., 1999; Kolukisaoglu et al., 2004;
Weinl and Kudla, 2009). CBL-CIPK complexes have recently been
implicated in sodium, potassium, nitrate, and proton transport
(Li et al., 2006; Xu et al., 2006; Ho et al., 2009); therefore the CBLCIPK network is currently thought to be a major regulator of ion
homeostasis in angiosperms.
Though CBLs and CIPKs have been discovered among all studied land plants and certain green algal lineages, little is known
about the functionality of the CBL-CIPK network outside of
angiosperms. As an initial step toward functional analysis of the
CBL-CIPK network in an early-diverging land plant, we analyzed the genomic content of CBLs and CIPKs in the model

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

moss Physcomitrella and performed bioinformatic analyses of the
CBL and CIPK families with an emphasis on relationships among
Physcomitrella and Arabidopsis CBLs and CIPKs. We classified
CBLs according to their phylogeny and N-terminal localization
motifs and identified three ancient classes of CBLs. Using yeast
two-hybrid analyses, we confirmed interactions among CBLs
and CIPKs outside of angiosperms and characterized physical
interactions among Physcomitrella CBLs and CIPKs. Through
phylogenetic analyses, we identified a strongly supported clade
that contains all CIPKs identified from green algae and two CIPKs
from Arabidopsis and Physcomitrella. Using phylogenomic methods, we seek to characterize patterns of expansion of the CBLCIPK network among land plant lineages to classify CBLs and
CIPK in an evolutionarily and functionally meaningful manner
to facilitate functional genetic work in early-diverging plants.

MATERIALS AND METHODS
HOMOLOG IDENTIFICATION, SEQUENCE ALIGNMENT, AND
BIOINFORMATIC ANALYSES

CBL and CIPK homologs were identified using BLASTp and
tBLASTn searches of the Uniprot and the NCBI protein and
nucleotide databases, using previously identified CBLs and CIPKs
from Arabidopsis as queries. Additional sequences were manually
retrieved by annotation from UniProt using the keywords “calcineurin” and “CBL-interacting” (Jain et al., 2009). Genomic loci
of CBL and CIPK homologs in Physcomitrella patens were identified in version 1.6 of the Physcomitrella genome, available at
http://cosmoss.org (Zimmer et al., 2013). All charophyte CBL and
CIPK sequences identified were predicted by assembly of homologous expressed sequence tags (ESTs) from transcriptome-level
sequencing of diverse, representative charophyte genera (Timme
and Delwiche, 2010; Timme et al., 2012). Other new CBL and
CIPK protein sequences were predicted from EST sequences in
the NCBI non-redundant (nr) nucleotide database identified
by tBLASTn searches. Overlapping ESTs from the same taxa
were assembled, and ESTs were translated using Geneious R6
(Biomatters), which was also used for all stages of phylogenetic analyses and figure preparation. Predicted CBL and CIPK
homologs were verified by manual inspection of domain architecture and pBLAST searches of the NCBI non-redundant (NR) protein database; all protein sequences included in analyses showed
expected domain architecture and yielded top BLASTp hits to
previously identified CBLs and CIPKs. CBL and CIPK homologs
identified in this study are listed in Supplementary Tables S1, S2,
respectively. Protein sequences were aligned using MAFFT (algorithm G-INS-i) and edited and trimmed by eye to remove short,
ambiguously aligned regions (see Supplementary Files S1,S2).
Edited alignments were used to generate the phylogenetic trees
shown Katoh et al. (2002). Phylogenetic trees were generated from
the resulting multiple sequence alignments (MSAs) using PhyML
with subtree pruning and regrafting (SPR) + nearest neighbor
interchange (NNI) moves and X2 -like approximate likelihood
ratio test (aLRT) clade support values, which serve as confidence
scores much like bootstrap scores. Clades with aLRT scores > 0.95
were deemed to have strong phylogenetic support (Anisimova
and Gascuel, 2006; Guindon et al., 2009). Specific model parameters are provided in the figure legend for each PhyML analysis

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presented, however several additional MSAs and evolutionary
models and parameters were tested for agreement with conclusions presented here (data not shown). Clades and evolutionary
relationships mentioned in the text appeared consistently in independent phylogenetic analyses with different model parameters
and MSAs.
CLONING AND SEQUENCING OF CBLs AND CIPK FROM THE MOSS
PHYSCOMITRELLA

In order to verify expression and expected splice patterns of
CBLs and CIPKs in an early-diverging land plant, we cloned
CBLs and CIPKs identified from the model moss Physcomitrella.
RNA was extracted from protonema and gametophores of
Physcomitrella patens ssp patens ecotype Gransden 2004 using
a CTAB/chloroform method similar to the one described by
Chang et al. (1993). The RNA was reverse transcribed to
produce cDNA using Superscript III Reverse Transcriptase
(Invitrogen). Primers containing Invitrogen Gateway attB1 (forward primers) and attB2 (reverse primers) recombination sites
were designed to amplify the coding sequences (CDSs) of each
Physcomitrella CBL (PpCBL) and CIPK (PpCIPK) genes (see
Supplementary Table S3 for oligonucleotide sequences used in
this study). CBL and CIPK transcripts were amplified using
Phusion DNA Polymerase (Thermo-Fisher Scientific) following
recommended manufacturer protocols on a MJ Research PTC100 or PTC-200 model thermocycler. PCR products were visualized on a 0.8% agarose gel, and products of the expected sizes
were extracted using a QIAquick gel extraction kit (Qiagen) and
cloned into the pDONR™/Zeo vector (Invitrogen) by Gateway
BP reaction, following manufacturer recommendations. Samples
from three or more clones for each gene were submitted to Elim
Biopharmaceuticals, Inc. (Hayward, CA) for DNA sequencing.
YEAST TWO-HYBRID ASSAYS

In order to verify physical interactions among CBLs and CIPKs in
a non-angiosperm plant, we cloned the CDS of each full-length
CBL and CIPK transcript identified in Physcomitrella and tested
interactions among PpCBLs and PpCIPKs in yeast two-hybrid
(Y2H) assays using the yeast strain AH109 (Clontech Inc.). This
strain is auxotrophic for leucine, tryptophan, histidine, and adenine. The CDSs of PpCBLs and PpCIPKs were cloned by Gateway
LR reaction into yeast two-hybrid gateway-compatible vectors
(pGBT9-BS-GW and pGAD-GH-GW) derived from pGBT9-BS
and pGAD-GH (Clontech). These vectors were transformed into
yeast cells using the G-Biosciences FastYeast Transformation Kit
and used to express CBL and CIPK fusions to the DNA-binding
domain (BD) and activation domain (AD) of a split transcription
factor. We screened CBL-BD fusions (pGBT9-BS-GW constructs)
for interactions with CIPK-AD fusion proteins (pGAD-GH-GW
constructs) and performed reciprocal screens among CIPK-BD
and CBL-AD fusion proteins to verify that the interactions were
not vector-dependent. As negative controls, we verified that
CBL-BD or CIPK-BD fusion proteins did not interact with the
pGAD-GH empty vector (EV).
To perform Y2H screens, co-transformed cells were cultured
to mid-log phase in MP Biomedical drop out base (DOB) liquid
media lacking leucine and tryptophan (-LT), to ensure retention

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

of vectors containing bait and prey constructs. We then adjusted
the cultures to OD600 = 0.05 and divided them into four 10-fold
dilutions (OD600 = 5 × 10−2 , 5 × 10−3 , 5 × 10−4 , 5 × 10−5 ).
6 µl droplets of each dilution were plated on agar DOB media
(1) lacking leucine and tryptophan (-LT) to serve as a positive control for transformation and loading, (2) lacking leucine,
tryptophan, and histidine (-LTH) to test for protein-protein interactions under low stringency, and (3) lacking leucine, tryptophan,
histidine, and adenine (-LTHA) to test for interactions under
stringent conditions. Cell growth was recorded at 48 h intervals
over the course of 6 days.

RESULTS AND DISCUSSION
CBL-CIPK NETWORK COMPOSITION IN GREEN ALGAE, MOSS, AND
OTHER LAND PLANTS

CBLs and CIPKs have been previously identified among various land plants and chlorophyte green algae, though other
chlorophytes appear to lack CBL-CIPK homologs (Weinl and
Kudla, 2009). Utilizing recently available transcriptome data, we
identified CBL and CIPK homologs from several charophyte
green algae species: Coleochaete orbicularis, Klebsormidium flaccidum, Chaetospheridium globosum, Penium margaritaceum, and
Chlorokybus atmophyticus. Interestingly, we identified a single
CBL and single CIPK in each of these lineages, with one exception. We could not confidently identify a CIPK homolog from
Chlorokybus, though this may due to incomplete transcriptome
coverage. Additional CBL or CIPK homologs may be present in
these taxa but undetected due to incomplete sequencing coverage, or additional homologs may simply not be transcribed at
sufficient levels under sampled growth conditions. In agreement
with our current understanding of evolutionary relationships
among these organisms, charophyte green algae sequences display
greater sequence similarity to land plant CBLs and CIPKs than
chlorophyte homologs. Although there is no currently available
genome sequence for any charophyte, only a single CBL and single CIPK were identified in the complete genome sequence of the
chlorophytes Ostreococcus lucimarinus and Bathycoccus prasinos,
consistent with prior findings (Weinl and Kudla, 2009). Though
it is difficult to make genomic inferences about any charophyte
green alga without an available complete genome sequence, our
analyses suggest that green algae commonly contain a single CBLCIPK pair and that the CBL-CIPK network likely predates the
split of chlorophyte and charophyte algae.
All CBLs and CIPKs analyzed in this study, including the most
divergent homologs identified in algae, show strong conservation
of domain architecture and important motifs. At approximately
200 amino acids (AAs) in length, CBLs contain one of a few
variations of a localization at their N-termini, followed by 4
calcium-binding EF hand domains. The first EF-hand of CBLs
is distinctive in that the calcium-binding loop is comprised of
14 rather than 12 AAs, however evidence suggests that it indeed
binds calcium ions (Nagae et al., 2003). Identified full-length
CIPKs are approximately 475 AAs in length and have a conserved domain architecture comprised of a N-terminal kinase
domain and a C-terminal autoinhibitory region with a diagnostic
NAF domain that mediates interactions with CBLs. One previously identified CIPK from the chlorophyte green alga Chlorella

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(UniProt: C4P7Q5) differs, however, in that it possesses 2 NAF
domains in its C-terminus, though the significance and accuracy of the published domain architecture is unknown. Our
homology search results corroborate the assertion that CBLs and
CIPKs are not found in certain chlorophyte green algae, including the models Chlamydomonas and Volvox (Weinl and Kudla,
2009; Batistic et al., 2011). This pattern parallels trends in calcium channel evolution. The Chlamydomonas genome encodes
several voltage-dependent calcium channels (VDCCs) and transient receptor potential (TRP) channels, which play critical roles
in environmental sensing in metazoans, whereas sequenced land
plant genomes do not contain discernible homologs from either
family (Wheeler and Brownlee, 2008; Verret et al., 2010). Like
most metazoans, Chlamydomonas is motile and, in addition
to performing photosynthesis, readily grows heterotrophically.
Chlamydomonas cells contain an organelle unlike any found in
plants, the eyespot, that is involved in the calcium-mediated process of phototaxis (Witman, 1993). Based on these observations, it
appears that some components of the calcium signaling machinery of certain chlorophyte green algae, such as Chlamydomonas,
more closely resemble animal signaling networks in some aspects
than those of land plants.
Taking advantage of the published genome sequence of the
moss Physcomitrella patens, we determined the genomic complement of CBLs and CIPKs in this early-diverging model plant. We
identified a total 4 CBL and 7 CIPK predicted protein sequences in
Physcomitrella, consistent with prior reports (Batistic̆ and Kudla,
2009; Weinl and Kudla, 2009). One pair of CBLs (PpCBL2+3) and
three pairs of CIPKs (PpCIPK1+5, 3+4, and 6+7) showed strikingly high sequence similarities at both the amino acid (73–93%
pairwise identity) and genomic level (42–52% pairwise identity).
Because of this observation and the inferred whole genome duplication (WGD) estimated to have occurred ∼45 million years ago
in Physcomitrella (Rensing et al., 2007), we hypothesized that pairs
of CBLs and CIPKs are products of the recent WGD and that the
“unpaired” CBLs (PpCBL1 and PpCBL4) and CIPK (PpCIPK2)
may similarly possess cognate loci in the Physcomitrella genome.
Consistent with this hypothesis, we identified paired loci for
each gene and provisionally named these PpCBL5, PpCBL6, and
PpCIPK8 (Figure 1). Although these loci showed relatively low
percentage identity to their cognate loci compared to previously detected CBLs and CIPKs, gene predictions using Augustus
(Stanke et al., 2004) suggested these loci may encode partial or
full-length proteins. Using RT-PCR, we amplified and cloned
transcripts from PpCBL5 and PpCIPK8, however we failed to
amplify transcripts from the PpCBL6 locus using several primer
pairs validated on genomic DNA (data not shown), despite testing
cDNA from different developmental stages (protonema, gametophores, sporophytes). Pairwise alignment of the PpCBL4 and
PpCBL6 loci revealed a relatively low percentage identity, particularly in PpCBL4 exonic regions, compared to other “sister” pairs
of CBLs and CIPKs; these observations suggest that PpCBL6 may
be a pseudogene. Sequenced PpCBL5 and PpCIPK8 transcripts
detected from both gametophyte and sporophyte cDNA were
found to contain premature termination cassettes (PTCs) in their
spliced forms (see Figure 1, Supplementary File S3), which suggests that these transcripts may not be translated, at least under

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conditions that we tested. Physcomitrella CIPK8 contains a single
nucleotide repeat (SNR), which are known to promote mutations and quickly change in length (Ellegren, 2004), spanning 31
bases in the retained PTC in cloned transcripts, further marking
it as an unusual CIPK. Interestingly, PpCBL5 and PpCIPK8 show
obviously stronger conservation in exonic regions (i.e., regions
retained in spliced transcripts and that align to their sister gene’s
CDS) than intronic or regulatory regions (i.e., promoter and terminator). While these aberrant CBL and CIPK loci may simply
be in early stages of pseudogenization, the unexpected finding
that these loci are transcribed and spliced warrants further investigation into possible functions and may point toward a role
for these transcripts as regulatory RNAs, as shown previously
in animals (Korneev et al., 1999; Hirotsune et al., 2003; Tam
et al., 2008). Like in Physcomitrella, expansion of the CBL-CIPK
network in Arabidopsis, previously attributed to segmental duplications (Kolukisaoglu et al., 2004), can be traced to known WGD
events in light of our current understanding of plant genome evolution (Cui et al., 2006). Independent expansion of other gene
families in moss and angiosperms has been described, and this
can obfuscate direct comparison and functional prediction of
genes in widely divergent plants (Cui et al., 2006; Bowman et al.,
2007; Rensing et al., 2008; Jiao et al., 2011).
PHYLOGENOMIC ANALYSIS OF CBL REVEALS CONSERVATION OF
THREE UNIQUE N-TERMINAL MOTIFS

Phylogenomic methods extend the ability to determine relationships among distant homologs, facilitate functional prediction,
and provide a framework for discovery of key features by identifying conserved regions of proteins (Eisen and Wu, 2002; Sjölander,
2004). Using maximum likelihood (ML) methods, we reconstructed the phylogeny of the CBL family in green lineages.
Consistent with our hypothesis that land plant CBLs and CIPKs
expanded from a simple module present in their common ancestor with algae, green algal CBLs cluster closely to one another
with high confidence scores in phylogenetic analyses. Although
algal CBLs do not consistently cluster with any particular clade
of CBLs from land plants, they commonly show moderate phylogenetic affinity for a clade containing Arabidopsis CBL1 and
CBL9 (Figure 2; see Supplementary Figure 1 for full tree), which
play important roles in potassium nutrition through regulation
of the AKT1 channel. Like Arabidopsis CBL1 and CBL9, green
algal CBLs feature the dual-lipid modification motif MGCXXS/T
or obvious relicts of this motif. Due to the retention of this motif
among many embryophyte and green algal CBLs and the results
of our phylogenetic analysis, we hypothesize that the dual-lipid
modification motif is the ancestral localization mechanism of
CBLs. This hypothesis is strengthened by the observation that
distantly homologous neuronal calcium sensor (NCS) proteins
feature a similar N-terminal motif (MGXXXS) that lacks the conserved cysteine residue but does trigger N-myristoylation of the
conserved glycine residue (Li et al., 2011). We designate homologs
with the dual lipid modification motif as Type I CBLs (Figure 3
top). Consistent with the hypothesis that ancestral CBLs most
closely resembled modern Type I homologs and gave rise to other
types of CBLs, Type I CBLs are paraphyletic with respect to
other CBLs. Arabidopsis CBLs containing the Type I dual lipid

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FIGURE 1 | Pairs of cognate CBLs (top) and CIPKs (bottom) in the
Physcomitrella genome aligned using MAFFT. Displayed pairs of CBLs
and CIPKs are genomic loci that are reciprocal best BLASTn hits within the
genome, and inferred phylogenetic relationships are indicated by
cladograms and described in the main text. Pairwise percentage nucleotide
(nt) identity for pairs of genomic loci are displayed in boxes. Aligned
nucleotides are displayed as bars shaded proportionally to percentage
identity, and gapped regions in the alignment are represented by lines. Bar
graphs indicate percentage identity (sliding window = 6 nt). Genes with
cloned transcripts that do not encode full-length proteins under tested
conditions are indicated with an asterisk (∗ ) and genes lacking detectable
transcripts are marked with two asterisks (∗∗ ). In cases where our

modification motif have been shown to localize to the plasma
membrane (D’Angelo et al., 2006; Cheong et al., 2007; Batistic
et al., 2008). Mutational analyses using FP-fusions indicate that
both N-myristoylation and S-acylation are required to target

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

experimentally inferred gene model did not match the annotation, verified
exons (blue), alternatively spliced regions (cyan), and premature termination
cassettes (PTCs; red) are shown for comparison. CIPK8, which was
annotated incorrectly as three separate transcripts, contains a long single
nucleotide repeat (SNR) comprised of 31 thymidine (T) residues and
described further in the main text. Sequences and associated annotations
were extracted from the Physcomitrella genome v1.6 starting from 500
nucleotides (nt) upstream of the annotated 5 UTR (750 nt upstream CDS
for genes lacking 5 UTR annotations) to 250 nt downstream of the
annotated 5 UTR (500 nt downstream the CDS) were extracted. Pairwise
loci were aligned using MAFFT. Although PpCBL6 has annotated exons,
there is no experimental evidence that any part of this locus in transcribed.

proteins to the plasma membrane, whereas either modification
on its own results in endomembrane localization (Batistic et al.,
2008). Although subcellular localization has not been investigated
in early diverging plants or green algae, we speculate that the

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FIGURE 2 | Maximum Likelihood (ML) phylogenetic tree derived from
multiple sequence alignment (MSA) of all CBL amino acid (AA)
sequences analyzed in this study. Chlorophyte and charophyte green algal
CBL and CIPKs are highlighted in green, and clades containing Type I–III

ancestral CBL-CIPK module may have participated in the regulation of integral membrane proteins at the plasma membrane,
given the observed evolutionary trends and our understanding of
CBL-CIPK function and biochemistry in Arabidopsis.
Phylogenetic analyses revealed a strongly supported (aLRT =
1.0) clade that contains Physcomitrella CBL2 and CBL3
and Arabidopsis CBL2, CBL3, CBL6, and CBL7 (Figure 4).
Physcomitrella CBL2 and CBL3 encode proteins that are 76%
identical, and both genes lack introns, unlike other CBLs from
Arabidopsis or Physcomitrella. The clade also contains homologs
from other non-angiosperms, including three CBLs from the
lycophyte Selaginella moellendorffii. Like Arabidopsis, Selaginella
CBLs in this clade contain multiple introns and exhibit a
conserved exon-intron structure (data not shown), leading us
to infer there was a likely reverse transcription event in the
Physcomitrella lineage not shared with the lineage leading to lycophytes and angiosperms. Experimental work is needed to determine functional consequences of intron loss in Physcomitrella
CBL2 and CBL3, however the effects and mechanisms of reverse
transcription-mediated intron loss events and other means of
intron loss are discussed elsewhere (Jeffares et al., 2006; Filichkin
et al., 2010). Based on high sequence similarity, shared intron
loss, and strong phylogenetic evidence, we infer that PpCBL2
and PpCBL3 are products of a lineage-specific gene duplication,
likely the results of a recent WGD (Rensing et al., 2007, 2013).
Both genes are orthologous to the four Arabidopsis CBLs contained in this clade. Arabidopsis CBL2 and CBL3 are also recent
duplicates, as evidenced by their phylogenetic placement and very
high sequence similarity (∼92% AA identity) throughout their
entire lengths. CBL3 and CBL7 are tandem duplicates, although

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CBLs identified in this study are annotated. The yellow star indicates an
inferred intron loss event. See Supplementary Table S1 for list of CBL
sequences used in this study, Supplementary File S1 for MSA, and
Supplementary File S2 for full phylogenetic tree.

CBL7 is disparate from other Arabidopsis CBLs and contains a
deletion in its N-terminus between a degenerate dual-lipid modification motif and its first EF hand (Batistic̆ and Kudla, 2009).
Arabidopsis CBL6, which features an unusual first EF hand relative to other CBLs, is more distantly related to the three other
AtCBLs in this clade and forms a clade with orthologous CBLs
from other eudicots.
Arabidopsis CBL2, CBL3, and CBL6 have been reported to
localize to the tonoplast (Batistic̆ and Kudla, 2009). In the case
of CBL2 and CBL3, it has been rigorously shown that an Nterminal motif known as the tonoplast targeting sequence (TTS)
mediates its subcellular localization (Tang et al., 2012). The
TTSs of Arabidopsis CBL2 and CBL3, with the consensus motif
MSQCXDGXKHXCXSXXXCF, span 19 AA; and the last three
positions of the motif overlap with positions 2–4 in the dual
lipid modification motif of Type I CBLs (i.e., MGCXXS/T), sharing a conserved cysteine residue found in all CBLs analyzed (see
Figure 3, Supplementary File S1). This 19-AA fragment from
either Arabidopsis CBL2 or CBL3 is necessary and sufficient for
targeting of FP fusions to the tonoplast in Arabidopsis mesophyll
cells (Tang et al., 2012), and strong sequence similarity suggests
that CBL6 shares this targeting mechanism (Figure 3 middle).
CBL7 is reported to show a diffuse nuclear and cytosolic localization based on the analysis of fluorescent fusion proteins (Batistic
et al., 2008), however we are unaware of any rigorous attempts
to determine its subcellular localization. Therefore, it appears
that tonoplast localization is a generally conserved feature among
angiosperm CBLs in this clade. We identified a TTS-like motif
in all three Selaginella CBLs in this clade and in PpCBL3. Unlike
PpCBL3, PpCBL2 does not contain an extended N-terminus and

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FIGURE 3 | CBL N-terminal localization motifs can be classified into
three ancient types. Consensus sequences are provided above each MSA,
and degree of conservation is indicated by bar graph and shading. Note the
strictly conserved cysteine residues (green dots) in all three types of CBLs.
(Top) Type I CBLs harbor a dual-lipid modification motif (MGCXXS/T) that
triggers N-myristoylation of the glycine residue and S-acylation of the
cysteine residue. Most green algal CBLs identified to date are Type I CBLs or
appear to retain signatures of the dual-lipid modification motif. (Middle) Type
II CBLs are characterized by a N-terminal extension called the TTS that is

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

found in nearly all CBLs contained in the Type II clade. Phylogenetic evidence
suggests that PpCBL2 has lost its TTS through a mechanism such as gene
conversion. (Bottom) Type III CBLs feature a long N-terminal extension that is
predicted to constitute a transmembrane helix. Residues are colored
according to hydrophobicity (red) or hydrophilicity (blue), and mean
hydrophobicity and similarity are indicated by bar graphs. Although PpCBL4
does not cluster with seed plant CBLs that share a similar N-terminal
extension, we propose that it is targeted in a similar manner to other Type III
CBLs based on sequence analysis of its N-terminal extension.

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FIGURE 4 | Close-up of Type II CBL clade from ML tree shown in Figure 2.
Confidence scores (aLRT) are shown for each clade, and the yellow star
denotes an inferred intron loss event. Some clades are unlabeled or collapsed
for clarity (see full tree in Supplementary File S2). Type II CBLs are
distinguished by the presence of an N-terminal tonoplast targeting sequence
(TTS), however certain members (asterisks) of the Type II clade have lost or

instead contains the Type I dual lipid modification motif. Given
these trends, we posit that the TTS is a synapomorphy of this clade
and that PpCBL2 lost its TTS via deletion or partial gene conversion, as described elsewhere (Jeffares et al., 2006). Based on strong

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

degenerate TTSs. Arabidopsis CBLs in this clade (green dots) contain the TTS
or a degenerate form of it; whereas the two Physcomitrella CBLs (yellow
dots) in this clade sharply differ in that CBL2 has a Type I dual-lipid
modification motif and CBL3 has a TTS. Presence of the TTS in Selaginella
homologs within the clade (see Figure 3) suggests that CBL2 has lost its
TTS, through a mechanism such as gene conversion, for example.

phylogenetic support and TTS motif conservation, we designate
homologs contained in this clade as Type II CBLs.
Phylogenetic analyses also identified a strongly supported
clade that contains Arabidopsis CBL10, the only Arabidopsis CBL

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FIGURE 5 | Close-up of Type III CBL clade from ML tree shown in
Figure 2. Confidence scores (aLRT) are shown for each clade. Arabidopsis
CBL10 (green dot) and orthologs in angiosperms and gymnosperms that
share the presence of a single N-terminal transmembrane helix (see

predicted to contain a transmembrane (TM) helix for membrane
association (Figure 5). This clade contains orthologs from all
studied angiosperms and gymnosperms, indicating this clade is
conserved among seed plants; and all members of this clade with
full-length sequences exhibit a predicted N-terminal transmembrane helix. Like members of the AtCBL10 clade, Physcomitrella

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

Figure 3) form a well-supported clade (aLRT = 0.96). Physcomitrella CBL4,
which also appears to contain a N-terminal transmembrane helix, does not
phylogenetically cluster with this clade or other angiosperm homologs,
possibly due to sparse taxon sampling among bryophytes.

CBL4 contains an extended N-terminus, which we posited may
form a transmembrane helix (Figure 3 bottom). Various TM
topology prediction methods disagree on whether AtCBL10 or
PpCBL4 contain a predicted TM helix (data not shown), however
visual inspection of hydrophobicity and patterns of conservation in MSAs suggests that both AtCBL10 and PpCBL4 contain

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FIGURE 6 | The CBL-interacting or NAF motif is
green algal and moss CIPKs. Consensus amino
this motif and degree conservation, illustrated by
provided above the MSA, which is shaded based

Comparative phylogenomics of the CBL-CIPK calcium-decoding network

conserved in
acid sequence of
bar graph, are
on the degree of

FIGURE 7 | Heat map summarizing yeast two-hybrid (Y2H) results for
all Physcomitrella CBL and CIPK combinations. Each CBL and CIPK was
fused to activation domain (AD) or DNA-binding domain (BD) of a split
transcription factor and screened for interactions between CBL-AD/CIPK-BD
fusion proteins and CBL-BD/CIPK-AD fusions. Interaction strength was
inferred by serial growth dilutions on selective media lacking one or two
auxotrophic markers and summarized qualitatively by heat map. Red boxes
indicate vigorous growth on -LTHA plates (see Materials and Methods);
orange boxes indicate weaker growth on -LTHA plates. Yellow boxes
indicate robust growth on -LTH plates but no growth on -LTHA plates. Gray
boxes indicate weak growth on -LTH plates, but each CBL-CIPK interaction
conferred better growth than the empty vector (EV) control. Representative
images of each assay are shown in Supplementary Figure S3. Inferred
phylogenetic relationships of Physcomitrella CBLs and CIPKs are indicated
by cladogram and described in the main text.

N-terminal TM helices. The presence of this TM helix raises the
possibility that PpCBL4 may be an AtCBL10 ortholog, however
our phylogenetic data neither favor nor disfavor this hypothesis.
More thorough coverage of sequence data from early-diverging

Frontiers in Plant Science | Plant Genetics and Genomics

AA conservation. Strong conservation of this motif, responsible for
CIPK interactions with CBLs, suggests that CBLs and CIPKs
identified from green algae and early-diverging land plants constitute
a functionally linked network.

plants is likely required to test this possibility and determine
whether Type III CBLs are monophyletic or not. The Arabidopsis
CBL10 transcript is reportedly processed into mRNAs that encode
proteins with two distinct N-termini, though both share the same
TM helical region. Alternative splicing is mediated by a unique
8th intron (other rice and Arabidopsis CBLs contain 6 or 7
introns) toward the 5 pend of the transcript. Both Physcomitrella
CBL4 and Arabidopsis CBL10 share a very similar exon-intron
structure (data not shown), though we did not find evidence of
alternative splicing in PpCBL4.
The typically short length and strong structural conservation
of EF hand proteins like CBLs can complicate phylogenetic reconstruction, as relatively few substitutions can significantly influence results. Due to biophysical constraints, EF hand domains
typically exhibit strong sequence conservation at positions that
coordinate calcium ion binding. However, variation seen among
EF hands of CBLs are predicted to have widely differing affinities
for calcium ions, thereby facilitating functional diversity at the
level of calcium binding. The 4th EF hand (EF4) of Physcomitrella
CBL4 is unusual in that it contains non-polar residues at two of
the positions that coordinate calcium ion binding, rather than
negatively charged residues as seen in virtually all other EF hands.
Therefore, it appears likely that it does not bind calcium. Indeed,
studies of other calcium signaling pathways have underscored the
plasticity of signaling components during evolution. The model
yeast Saccharomyces cerevisiae contains a single-copy gene encoding a calmodulin (CaM), a widely studied type of calcium sensor
in eukaryotes. This gene, CMD1, is indispensable for survival
of the cell. Surprisingly, molecular genetic analysis suggests the
CaM’s ability to bind calcium ions is dispensable for its most
vital functions, and its fourth EF hand is unable to bind calcium
(Cyert, 2001). Plants contain a suite of typical CaMs and widely
divergent CaM homologs, some of which either lack the ability
to bind calcium ions or coordinate them in an unusual manner

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(McCormack and Braam, 2003). Further work is needed to clarify
the capacity and affinity of identified CBLs for calcium binding,
particularly among non-angiosperm CBLs.
There has been some debate as to the localization of
Arabidopsis CBL10; various reports indicate localization to the
tonoplast (Kim et al., 2007; Batistic et al., 2010) or plasma membrane (Quan et al., 2007; Ren et al., 2013). Although the multiple
isoforms of CBL10 may account for different localization patterns, Arabidopsis CBL10 is most strongly expressed in shoots
and is suggested to participate in the regulation of a NHX-family,
Na+ /H+ exchanger believed to function in the sequestration of
sodium ions within the vacuole. A model has emerged wherein
CBL10 plays a regulatory role in the SOS pathway akin to that
of CBL4/SOS3 (Kim et al., 2007; Tang et al., 2013). In root
hair and cortical cells, the Type I Arabidopsis CBL4 forms a
complex with CIPK24, and together they regulate the activity
of the plasmalemma-localized Na+ /H+ exchanger SOS1 (syn.
NHX7) and facilitate the extrusion of sodium ions from the plant.
In shoot mesophyll cells, CBL10 complexes with CIPK24, and
together they putatively regulate the activity of an unidentified
tonoplast-localized Na+ /H+ exchanger and facilitate sequestration of sodium ions in the vacuole. A recent publication proposes
a role for CBL10 in the regulation of the plasmalemma-localized
potassium channel AKT1 (Ren et al., 2013), which has been rigorously shown to be subject to regulation by CBL1 and CBL9 acting
in concert with CIPK23 (Li et al., 2006; Xu et al., 2006). Our phylogenetic results indicate that the single-pass N-terminal TM helix
is a synapomorphy of the AtCBL10 clade. Physcomitrella CBL4
likewise contains a N-terminal TM helix and may be orthologous,
therefore we designated these homologs Type III CBLs.
Different membranes of the eukaryotic cell have distinct
phospholipid profiles, which can serve as a basis for subcellular targeting. Moreover, each particular membrane is commonly composed of distinct microenvironments with unique
lipid and protein populations. Together, proteins and lipids are
thought to form functional modules in cellular membranes, with
membrane-targeted kinases recognized as common regulatory
modules (Engelman, 2005). For these reasons, we expect that
CBL-CIPK complexes are likely targeted not only to specific
membranes but to precise sites within membranes where they
interact and function with molecular partners (Bhatnagar and
Gordon, 1997; Levental et al., 2010). Elevation of free calcium
in the cytosol is localized and transient, partly due to effects of
Ca++ -ATPases and Ca++ /H+ antiporters and proteins that act
as buffers. Because calcium signatures occur locally, calcium sensors must operate in close proximity to the channels responsible
for calcium elevation (Fogelson and Zucker, 1985; Gilroy et al.,
1993; Roberts, 1994; Clapham, 2007). In light of this, we interpret the conservation of CBL localization motifs among distantly
related plants as a likely consequence of constraints on CBL-CIPK
subcellular localization.
Although several studies have examined CBL localization, it
remains unclear whether CBLs display a predominantly static or
dynamic localization at protein maturity. Our analyses demonstrate that the cysteine residue occupying the third position in
the Type I motif (MGCXXS/T) is perfectly conserved among
CBLs from widely divergent organisms and paralogous clades.

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

In Type I and Type II CBLs, this residue has been shown to be
S-acylated, and the modification is required for known protein
functions (Batistic et al., 2008; Batistič, 2012; Tang et al., 2012).
Based on its striking conservation, we predict that S-acylation of
this conserved residue is a shared among CBLs, at least under
certain conditions. It is well established that S-acylation is a
reversible post-translational modification and that it can strongly
impact protein localization and can be critical for protein function (Bijlmakers and Marsh, 2003; Hemsley and Grierson, 2008).
Prior research has pointed toward a role for S-acylation in finelevel targeting of proteins to specific membrane microenvironments (Bhatnagar and Gordon, 1997; Mumby, 1997; Dunphy and
Linder, 1998; Levental et al., 2010). We predict that N-terminal Sacylation at this conserved residue functions, at least in part, as a
mechanism for precise and dynamic localization of CBLs.
CONSERVATION OF THE NAF MOTIF AND CBL-CIPK INTERACTIONS IN
PHYSCOMITRELLA

The CBL-CIPK network is mediated by a conserved CBLinteracting domain (also known as the NAF or FISL motif) in
CIPKs. Our MSA of the CIPK family indicates that the NAF
domain is strongly conserved, with many identical residues,
among algal CIPKs and all CIPKs from Arabidopsis and
Physcomitrella (Figure 6). This observation is consistent with
our prediction that CBLs and CIPKs from green algae and
early diverging embryophytes function together as a module. To
confirm our presumption that Physcomitrella CBLs and CIPKs
physically interact with each other and lend support to our interpretation of these protein families as functionally connected in
early-diverging plants, we performed Y2H screening and characterized physical interactions between full-length PpCBLs and
PpCIPKs in yeast cells.
Consistent with our expectations, CBLs and CIPKs from
Physcomitrella showed physical interactions in yeast cells. All
combinations of PpCBL and PpCIPK fusion proteins showed
physical interactions in yeast (Supplementary Figure S2), but specific CBL-CIPK combinations showed very strong interactions
with select partners, consistent with the hypothesis that particular CBLs show preferential interactions with cognizant CIPKs
(Figure 7). We observed that “creeter” CIPKs displayed overlapping, though not identical, interaction profiles with their most
closely related homolog. CIPK1 and CIPK5 interact moderately
with CBL2 and CBL4 and weakly with CBL1 and CBL3. CIPK3
and CIPK4 interact weakly with CBL3 but moderately to strongly
with CBL1, 2, and 4. CIPK6 and CIPK7 interact strongly with
CBL4 and weakly to moderately with CBL1, 2, and 3. We observed
only weak interactions between CIPK2, which lacks a “sister”
CIPK, and any CBL, despite conservation of its NAF domain
and phylogenetic proximity to the highly interactive CIPK3 and
CIPK4.
Among the CBLs, CBL4 shows the highest number of strong
connections to CIPKs, and it interacts very strongly with CIPK6
and CIPK7, members of the green algal clade of CIPKs. CBL1, a
Type I CBL without clear phylogenetic affinities to angiosperm
CBLs, most strongly interacts with CIPK4 and shows very weak
interactions with CIPK1 and CIPK5. CBL3 shows clearly weaker
interactions with CIPKs than its close paralog CBL2, although

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FIGURE 8 | ML phylogenetic tree derived from protein MSA of all CIPKs
identified in this study. Confidence scores (aLRT) are shown for select
clades. CIPKs from green algae phylogenetically cluster with land plant
CIPKs, including Physcomitrella CIPK6 and CIPK7. Remaining Physcomitrella
CIPKs cluster with Arabidopsis CIPK1, 17, and 21, which contain multiple

their interaction profiles are similar. CBL2 and CBL3 both interact most strongly with CIPK3, CIPK4, and CIPK6. These data
support the model of a highly interconnected signaling network,
however interaction patterns may differ significantly in moss cells
due to differences in post-translational modifications, subcellular localization, expression, and other factors. Nonetheless, these
results provide a guide for genetic analyses in moss and lend
confidence to the interpretation that CBLs and CIPKs are functionally linked in early-diverging plants and constitute an ancient
signaling network.
PHYLOGENOMIC IDENTIFICATION OF THE ANCESTRAL OR “GREEN
ALGAL-TYPE” CLADE OF CIPKs

Phylogenomic analyses of the CIPK family were pursued, as
described for CBLs, to decipher evolutionary patterns to facilitate
identification of functionally meaningful groups, which would be
expected to show conservation across diverse land plants. Our
phylogenomic analyses of CIPKs (Figure 8; see Supplementary
Figure S3 for full tree) indicated most Arabidopsis CIPKs (18 of
26) are contained within an “intronless” clade (although CIPK16
contains a single intron that is inferred to be from an introngain event), consistent with prior analyses by Kolukisaoglu et al.

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

introns, and a clade of “intronless” CIPKs (although AtCIPK16 has gained
one intron) derived from an inferred reverse transcription event (yellow
star). See Supplementary Table S3 for CIPKs in this study, Supplementary
File S3 for MSA, and Supplementary File S4 for full phylogenetic tree with
tip labels. (∗ Although AtCIPK16 has gained one intron.)

(2004). We used conifer protein sequences from this clade as
queries for tBLASTn searches of Picea chromosomal sequences
(available at http://congenie.org) and did not identify introns
in expected locations for intron-containing CIPKs (data not
shown). Based on these observations, we posit that a reverse
transcription event occurred before the split of gymnosperms
and angiosperms and is a conserved feature of this clade. All
Physcomitrella CIPKs contain multiple introns, and none cluster with the intronless clade. Physcomitrella CIPK1—CIPK5 share
high sequence similarity (83–93% pairwise); and in our analyses,
they were placed with strong confidence in a clade with homologs
from other mosses, indicating they are paralogs in respect to
their closest seed plant homologs. This clade of moss homologs
is likely orthologous (aLRT = 0.97) to three clades of CIPKs conserved across seed plants: the aforementioned intronless clade, a
clade containing AtCIPK21, and a clade containing AtCIPK1 and
AtCIPK17.
Arabidopsis CIPK3+CIPK26, CIPK9, and CIPK23 each represent strongly supported (aLRT = 1.0; see Supplementary
Figure S3) clades that cluster with one another and contain
homologs in fully sequenced angiosperm genomes and, at least
for the CIPK3 + CIPK26 and CIPK23 clades, in gymnosperms.

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Whereas CIPK9 and CIPK23 regulate potassium transport and
function in root and shoot tissues (Cheong et al., 2007; Pandey
et al., 2007), CIPK3 has been implicated in abscisic acid (ABA)dependent regulation of seed germination (Pandey et al., 2008),
therefore homologs from seed plants as distantly related as gymnosperms might conceivably have a conserved regulatory role in
seeds, given their strong conservation.
Physcomitrella CIPK6 and CIPK7 belong to a clade that contains Arabidopsis CIPK8 and CIPK24 and, importantly, contains
all green algal CIPKs identified (Figure 9) with high confidence

FIGURE 9 | Close-up of the “green algal-type” CIPK clade from ML tree
shown in Figure 8. Confidence scores (aLRT) are shown for each clade.
Phylogenetic evidence strongly supports the existence of a clade
(aLRT = 1.0) containing all CIPK homologs identified from chlorophyte and
charophyte green algae, as well as two CIPKs each from Physcomitrella

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

(aLRT = 1.0). Although Physcomitrella and Arabidopsis each
contain two homologs in this clade, Physcomitrella CIPK6 and
CIPK7 (72% AA pairwise identity) are the products of a gene
duplication that occurred after the split between mosses and the
lineage leading to vascular plants. In contrast, Arabidopsis CIPK8
and CIPK24 (60% pairwise identity) each represent a separate,
strongly supported clade with orthologs in other angiosperms,
implying that they derive from duplications that occurred during seed plant (most likely angiosperm) diversification. Based on
our results, we posit that Physcomitrella CIPK6 and CIPK7 and

(yellow dots) and Arabidopsis (green dots). Physcomitrella CIPK6 and CIPK7
are recent paralogs and sister to one another in our analyses. In contrast,
Arabidopsis CIPK8 and CIPK24 each have clear orthologs in other sequenced
angiosperms, and these clades appear to have arisen from a gene duplication
that occurred around the time of divergence of angiosperms (arrow).

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FIGURE 10 | Key regulatory residues at the C-terminus of Arabidopsis
SOS1 (AtSOS1) are conserved in Physcomitrella homologs. The full-length
protein sequence alignment is shown on top with the zoomed in region
indicated by a shaded box. Arabidopsis CIPK24 (SOS2) phosphorylates the

Arabidopsis CIPK8 and CIPK24 (SOS2) most closely resemble
the ancestral or “green algal-type” CIPK and, due to their orthology, most likely to reflect ancestral function(s) of the CBL-CIPK
network.
Arabidopsis CIPK8 is believed to be a positive regulator of
the low-affinity phase of the primary nitrate response and has
been implicated in glucose sensing, although mechanistic details
are unknown at this time (Hu et al., 2009). Arabidopsis CIPK24,
the first functionally characterized CIPK, plays a critical function
in sodium tolerance through CBL4(SOS3)-modulated phosphorylation of the Na+ /H+ exchanger SOS1. There is substantial
evidence that orthologs of CBL4 and CIPK24 in other flowering plant lineages have similar functions (Martínez-Atienza
et al., 2007; Tang et al., 2010). Given the phylogenetic proximity of Arabidopsis CIPK24 to green algal CIPKs, future work
will test whether green algal CIPKs, and Physcomitrella CIPK6
and CIPK7, function in Na+ /K+ homeostasis or possibly more
broadly regulate ion transport. It has already been established
that two orthologs of SOS1 in Physcomitrella (PpSOS1 and
PpSOS1b) are required for proper K+ /Na+ ratios and sodium
tolerance (Quintero et al., 2011). Interestingly, a 6 AA Cterminal motif of AtSOS1 that is a phosphorylation substrate
of CIPK24 and a 14-3-3 protein-binding site is 100% identical
to PpSOS1 and 50% identical to PpSOS1b, and the target serine is conserved in both homologs (Figure 10). Physcomitrella
SOS1 has further been shown to confer enhanced NaCl tolerance when heterologously expressed in yeast, and the effect
is strengthened by coexpression with Arabidopsis CBL4 and
CIPK24 (Fraile-Escanciano et al., 2010). Collectively, these observations suggest that the SOS pathway is conserved across land
plants and may be conserved among some green algal lineages. Functional molecular analyses of CBLs and CIPKs in
early-diverging plant and algal lineages could provide core
insights and clarify the increasingly complex picture of calciumregulated abiotic stress responses in Arabidopsis and agricultural
species.

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

serine (S) residue marked in red in AtSOS1 and facilitates binding by a 14-3-3
protein. In Arabidopsis, these mechanisms are critical to plant sodium tolerance.
Strong sequence conservation suggest similar mechanisms may be in place in
Physcomitrella, though the cognate CBL-CIPK pair is currently unknown.

CONCLUSIONS
Prior publications (e.g., Batistic̆ and Kudla, 2009; Weinl and
Kudla, 2009) have mentioned the apparent expansion of the CBLCIPK network in terms of the total numbers of CBLs and CIPKs
found in algae and early diverging plants compared to their
angiosperm counterparts. Here, we present phylogenetic evidence that the CBL-CIPK network has expanded independently
in multiple plant lineages, including mosses and angiosperms. It
appears that the common ancestor of mosses and vascular plants
likely contained three CBLs distinguishable by N-terminal localization motifs, which likely are synapomorphies among ancient
CBL subfamilies. We have identified a clade of CIPKs containing all green algal homologs and two representatives from
Physcomitrella and Arabidopsis. Phylogenetic analysis demonstrates that the Physcomitrella and Arabidopsis members of this
clade are the products of independent gene duplications and the
earliest land plants likely contained a single homolog from this
clade. The concurrent pairing of CBLs and CIPKs in available
genomes and transcriptomes, the striking conservation of the
NAF domain, and our Y2H results all point toward a physically
and functionally connected CBL-CIPK network across plants and
algae.
The function(s) of CBL-CIPK pairs found in green algae
remains an open and intriguing question, and our identification of charophyte CBL-CIPK pairs expands the list of potential
models for this inquiry. The conspicuous expansion of the network in several land plant lineages appears to have been driven
largely by WGDs, and we hypothesize that duplicated members
were adapted for novel signaling pathways and precise roles in
particular cells and tissues. Research on molecular processes modulated by CBLs and CIPKs has intensified in recent years, and
researchers are beginning to investigate CBL-CIPK functions in
non-model angiosperm species. The field is prime for investigation of CBL-CIPK functions in earlier diverging land plants,
and research in this area will enhance our understanding of the
molecular evolutionary basis of the colonization of land by plants.

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FUNDING
This research is supported by a grant from the National Science
Foundation (to Sheng Luan).

ACKNOWLEDGMENTS
We thank Dr. Stefan Rensing and Ryan Melnyk for helpful discussions on moss biology and evolutionary reconstruction of gene
families and thank Dr. Peggy Lemaux for her mentorship and
efforts to make this research possible. We are grateful to Dr. Ruth
Timme for her assistance with the identification of charophyte
CBLs and CIPKs. We gratefully acknowledge an NSF Graduate
Research Fellowship Program fellowship to Thomas J. Kleist and
a Sponsored Projects in Undergraduate Research fellowship and
Biology Scholars Program awards to Andrew L. Spencley.

SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online
at: http://www.frontiersin.org/journal/10.3389/fpls.2014.00187/
abstract
Supplementary Table S1 | CBL sequences used in this study.
Supplementary Table S2 | CIPK sequences used in this study.
Supplementary Table S3 | Oligonucleotides used in this study.

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Comparative phylogenomics of the CBL-CIPK calcium-decoding network

Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 31 January 2014; accepted: 21 April 2014; published online: 14 May 2014.
Citation: Kleist TJ, Spencley AL and Luan S (2014) Comparative phylogenomics of the
CBL-CIPK calcium-decoding network in the moss Physcomitrella, Arabidopsis, and
other green lineages. Front. Plant Sci. 5:187. doi: 10.3389/fpls.2014.00187
This article was submitted to Plant Genetics and Genomics, a section of the journal
Frontiers in Plant Science.
Copyright © 2014 Kleist, Spencley and Luan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
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ORIGINAL RESEARCH ARTICLE
published: 05 June 2014
doi: 10.3389/fpls.2014.00248

Allele diversity for abiotic stress responsive candidate
genes in chickpea reference set using gene based SNP
markers
Manish Roorkiwal 1,2 † , Spurthi N. Nayak 1,3 † , Mahendar Thudi 1 , Hari D. Upadhyaya 1 ,
Dominique Brunel 4 , Pierre Mournet 5 , Dominique This 6 , Prakash C. Sharma 2* and
Rajeev K. Varshney 1*
1
2
3
4
5
6

International Crops Research Institute for the Semi-Arid Tropics, Hyderabad, India
University School of Biotechnology, Guru Gobind Singh Indraprastha University, Delhi, India
Agronomy Department, University of Florida, Gainesville, FL, USA
Etude de Polymorphisme des Génomes Végétaux, INRA, Evry, France
UMR AGAP, CIRAD, Montpellier Cedex, France
UMR AGAP, Montpellier SupAgro, Montpellier, France

Edited by:
Mukesh Jain, National Institute of
Plant Genome Research, India
Reviewed by:
David M. Rhoads, California State
University, USA
Shailesh Tripathi, Indian Agricultural
Research Institute, India
*Correspondence:
Prakash C. Sharma, University
School of Biotechnology, Guru
Gobind Singh Indraprastha
University, AFR 109, A-Block,
Dwarka Sec 16C, Delhi 110078, India
e-mail: prof.pcsharma@gmail.com;
Rajeev K. Varshney, Center of
Excellence in Genomics,
International Crops Research
Institute for the Semi-Arid Tropics,
Building No 300, Patancheru,
Hyderabad 502324, India
e-mail: r.k.varshney@cgiar.org
† These authors have contributed
equally to this work.

INTRODUCTION

Chickpea is an important food legume crop for the semi-arid regions, however, its
productivity is adversely affected by various biotic and abiotic stresses. Identification of
candidate genes associated with abiotic stress response will help breeding efforts aiming
to enhance its productivity. With this objective, 10 abiotic stress responsive candidate
genes were selected on the basis of prior knowledge of this complex trait. These 10 genes
were subjected to allele specific sequencing across a chickpea reference set comprising
300 genotypes including 211 genotypes of chickpea mini core collection. A total of 1.3 Mbp
sequence data were generated. Multiple sequence alignment (MSA) revealed 79 SNPs
and 41 indels in nine genes while the CAP2 gene was found to be conserved across
all the genotypes. Among 10 candidate genes, the maximum number of SNPs (34) was
observed in abscisic acid stress and ripening (ASR) gene including 22 transitions, 11
transversions and one tri-allelic SNP. Nucleotide diversity varied from 0.0004 to 0.0029
while polymorphism information content (PIC) values ranged from 0.01 (AKIN gene) to
0.43 (CAP2 promoter). Haplotype analysis revealed that alleles were represented by more
than two haplotype blocks, except alleles of the CAP2 and sucrose synthase (SuSy) gene,
where only one haplotype was identified. These genes can be used for association analysis
and if validated, may be useful for enhancing abiotic stress, including drought tolerance,
through molecular breeding.
Keywords: chickpea, abiotic stress, single nucleotide polymorphism, genetic diversity, candidate genes

Chickpea (Cicer arietinum L., 2n = 16), a self-pollinated, diploid
annual species which ranks second worldwide as a food legume
crop, is primarily a crop of developing countries contributing
to a larger part of human food and animal feed in these areas.
Chickpea is a major source of nutrients to a vegetarian diet as it
contain 20–30% protein, ∼40% carbohydrates and is also a good
source of several minerals like calcium, magnesium, potassium,
phosphorus, iron, zinc, and manganese. Global chickpea production is 11.6 million t from 12.3 million ha area with an average
yield of less than one t/ha (FAO, 2012), much lower than its estimated potential of 6 t/ha under optimum growing conditions.
Productivity of chickpea is adversely affected by several abiotic
stresses of which drought, heat and cold are the major constraints
affecting seed yield (Ruelland et al., 2002). Plant stress responses
are generally controlled by a network of specialized genes through
intricate regulation by specific transcription factors (Chen and
Zhu, 2004). Application of available approaches to improve crop
productivity under adverse environmental conditions requires a

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better understanding of the mechanisms involved during crop’s
response to abiotic stress. Genomic technologies and comparative genomics approaches that have emerged during the past
decade can be exploited to identify some of the genes involved in
drought tolerance mechanisms. Candidate genes for stress tolerance may be used in crop improvement programs directly (transgenic approach) or indirectly (through identification of linked
SNPs) (Schena et al., 1995; Kudapa et al., 2013). The “chickpea
mini core” comprising of 211 diverse genotypes (Upadhyaya and
Ortiz, 2001) is a subset of the core collection (Upadhyaya et al.,
2001) which represents the entire collection conserved in the
ICRISAT Genebank. The reference set (Upadhyaya et al., 2008)
includes four C. reticulatum genotypes and three C. echinospermum genotypes, but the majority (293 genotypes) is C. arietinum
(Upadhyaya et al., 2006).
Although several genes have been found to be involved in abiotic stress tolerance in other crops, few studies have been carried
out in chickpea. Candidate genes can be selected on the basis of
prior knowledge from mutational analysis, biochemical pathways
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Roorkiwal et al.

or linkage analysis of the trait of interest (Zhu et al., 2008). The
candidate genes we selected were; Snf-1 related kinase (AKIN),
amino-aldehyde dehydrogenase (AMADH), abscisic acid stress
and ripening (ASR) gene, a homolog of the DREB2A gene, known
as the CAP2 gene, dehydrin (DHN), drought responsive element binding protein (DREB), ERECTA, Myb transcription factor
(MYB), sucrose phosphate synthase (SPS), and sucrose synthase
(SuSy).
The AKIN (SNF1 related protein kinase) gene belongs to the
CDPK–SnRK superfamily, which serves as important regulators modulating fundamental metabolic pathways in response to
nutritional and environmental stresses in plants (Halford and
Hey, 2009). An AMADH gene in sorghum was found to be related
to osmotic stress tolerance, dehydration and salt stress tolerance
(Wood et al., 1996) and the activity of AMADH in response to
stress caused by mechanical damage in pea seedlings was evaluated by Petrivalský et al. (2007). AMADH is expected to play
a role in physiological processes and metabolic pathways controlling response to abiotic stresses by detoxification of toxic
aminoaldehydes (Stiti et al., 2011). ASR gene is a stress-inducible
gene that has been reported exclusively in plants and belongs to a
small gene family characterized by the presence of an ABA/WDS
domain. Members of the ASR gene family are induced by abscisic
acid (ABA), various abiotic stresses including water stress and
during the process of fruit ripening (Carrari et al., 2004). ASR
genes in various species respond to different abiotic stress factors
including drought, salt, cold and limited light (Joo et al., 2013).
Over-expression of ASR in transgenic Arabidopsis was shown to
increase tolerance to drought and salt and decrease sensitivity to
exogenous ABA (Yang et al., 2005). Characterization of the ASR
gene family in rice identified the ASR3 gene as a candidate for
association studies related to drought tolerance (Philippe et al.,
2010). The potential importance of the ASR1 gene in drought
tolerance in common bean was reported by Cortés et al. (2012a)
who found low nucleotide diversity suggestive of strong purifying
selection, in wild and cultivated accessions.
Dehydrins (DHNs) are among the most commonly observed
proteins induced by environmental stress associated with dehydration or low temperature (Hanin et al., 2011). The DHN
proteins have been estimated to comprise up to 4% of the total
seed protein, and are thought to be involved in protecting the
embryo and other seed tissues from osmotic stresses associated with the low water content of the mature seed (Wise and
Tunnacliffe, 2004). A positive correlation between accumulation
of DHN proteins and tolerance to freezing, drought, and salinity
has been shown (Close, 1996; Allagulova et al., 2003). Transgenic
plants overexpressing DHN showed better growth and tolerance
to drought and freezing stress compared to controls (Puhakainen
et al., 2004). DREB are transcription factors that induce a set of
abiotic stress-related genes and impart stress endurance to plants.
DREBs belong to the ERF (ethylene responsive element binding
factors) clade of the APETALA2 (AP2) family are distinctive to
plants. Transcription factors DREB1A/CBF3 and DREB2A were
identified as cold and drought stress–responsive genes expressed
in Arabidopsis thaliana (Sakuma et al., 2006). Constitutively activated DREB2A resulted in significant drought stress tolerance in
transgenic Arabidopsis plants and expression analysis revealed that

Frontiers in Plant Science | Plant Genetics and Genomics

Gene sequence diversity in chickpea

DREB2A transcriptionally regulates many water stress-inducible
genes (Sakuma et al., 2006). In rice, expression of OsDREB2A was
induced by dehydration and high-salt stresses (Matsukura et al.,
2010; Mallikarjuna et al., 2011). Based on physiological studies in
several crop species, the DREB2A transcription factor is one of
the most promising candidate genes for drought tolerance. Low
sequence diversity of DREB2A was found in five crop species studied; chickpea, common bean, rice, sorghum, and barley (Nayak
et al., 2009) as well as in studies of wild and cultivated common
bean (Cortés et al., 2012b).
The ERECTA gene codes for a protein kinase receptor which
mediates plants’ responses to disease, predation and stress.
ERECTA is involved in leaf organogenesis and reduces the density of stomata on the leaf under-surface, thereby reducing the
evapotranspiration. In Arabidopsis, the ERECTA gene has been
shown to control organ growth and flower development by promoting cell proliferation (Shpak et al., 2004). The contribution
of ERECTA gene toward water use efficiency was confirmed
using complementation assays on wilting mutant Arabidopsis
plants (Masle et al., 2005). The ZmERECTA genes from maize
are patented by Pioneer Hi-Bred International, Inc., which were
involved in improving plant growth, transpiration efficiency and
drought tolerance in crop plants (www.freepatentsonline.com/
y2008/0078004.html). The Myb transcription factor family constitutes the largest and diverse class of DNA-binding transcription
factors in plants (Riechmann et al., 2000). The roles of Myb
genes in response to biotic and abiotic stress have been studied
in a number of plant species (Romero et al., 1998; Du et al.,
2012; Volpe et al., 2013). SuSy, a glycosyltransferase, and SPS
are key enzymes involved in sugar metabolism. Sucrose-synthase
transcript and protein levels have been shown to be modulated
by dehydration and rehydration (Kleines et al., 1999) and the
Arabidopsis AtSUS3 gene in particular was shown to be strongly
induced by drought and mannitol, thus behaving as a marker of
dehydrating tissues (Baud et al., 2004).
Genetic diversity, representing the overall genetic makeup of
a species, serves as a basis for a population to adapt to changing environments (Ross-Ibarra et al., 2007). Single nucleotide
polymorphisms (SNPs) have gained much popularity in assessing the diversity because of automation and abundance. Though
biallelic SNPs are generally less informative than multi-allelic simple sequence repeats (SSRs), their sheer abundance makes the
development of high density SNP genetic maps possible, providing the foundation for subsequent population-based genetic
analysis (Rafalski, 2002). In addition, a SNP is of great importance if it affects gene function and the function of the gene
in stress response is known/understood and the SNP is associated with differences in plant performance. Assessing genetic
diversity for stress responsive candidate gene sequences leads to
the identification of a specific allele of the particular gene in
that species associated with performance in response to a corresponding abiotic stress. Such information can therefore be further
used in breeding programs to develop better varieties using modern molecular breeding approaches like marker assisted recurrent
selection (MARS) or gene pyramiding. Allelic diversity (richness),
one of the most important and commonly used estimators of
genetic diversity in populations, mainly depends on the effective

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Roorkiwal et al.

population size and past evolutionary history (Petit et al., 1998).
However, the number of alleles identified and their frequency distribution also depend on the genetic marker system used in these
investigations. In the present study, the allelic diversity of candidate genes for abiotic stress tolerance was assessed in the chickpea
reference set.

MATERIALS AND METHODS
PLANT MATERIAL AND DNA EXTRACTION

Young leaf tissues of each accession of the reference set from the
greenhouse grown plants were harvested and immediately stored
in 96-well plate and the total genomic DNA of all the genotypes was isolated using high-throughput mini- DNA extraction
method (Cuc et al., 2008). The quality and quantity of extracted
DNA was checked on 0.8% agarose gel. The DNA was normalized
to 20 ng/µl concentration for further use.
IDENTIFICATION OF ABIOTIC STRESS RESPONSIVE GENES AND
PRIMER DESIGNING

A set of 10 abiotic stress responsive genes conferring abiotic stress
tolerance in model plants (Arabidopsis and Rice) and other crop
species (Glycine max and Medicago spp.) were chosen based on
available literature (Table 1). Different approaches were used for
primer designing based on availability of gene sequence information in chickpea. In the first approach, heterologous primers
were designed for ASR, SuSy, and SPS genes from corresponding
Medicago sequences. The ERECTA gene in chickpea was isolated
using consensus/degenerate primers designed at INRA, EPGV,
France. In the second approach sequence-specific primers were
designed, where in chickpea homologs of genes were isolated
using chickpea ESTs developed for abiotic stress (Varshney et al.,
2009) and available in NCBI EST database (DbEST- http://www.
ncbi.nlm.nih.gov/dbEST/) (Roorkiwal and Sharma, 2012). The
details of primers used in isolation of abiotic stress responsive
candidate genes in chickpea are given in Table 1.
POLYMERASE CHAIN REACTION (PCR) AND SEQUENCING OF
AMPLICONS

In order to amplify these candidate genes and confirm their presence, a pilot experiment was set to sequence amplicons from eight
diverse genotypes of chickpea consisting of Annigeri, ICCV 2,
ICC 4958, ICC 1882, ICC 283, ICC 8261, ICC 4411, and ICC
10029. PCR was set up with 20 µl reaction mixture comprising
5 ng of template DNA, 5 picomoles each of forward and reverse
primers, 2 mM dNTP, 20 mM MgCl2 , 1X PCR buffer (AmpliTaq
Gold) and 0.25 U of Taq polymerase (Ampli Taq Gold). PCR
cycles comprising of denaturation of 94◦ C for 5 min, followed
by 40 cycles of 94◦ C for 30 s annealing at temperature specific
for each target gene for 40 s and 72◦ C for 1 min 30 s and a final
extension was carried out at 72◦ C for 20 min. The amplified product (about 2 µl) was loaded on 1.2% agarose. The remaining
PCR amplicons were purified using 1 unit of Exonuclease I and
1 unit of shrimp alkaline phosphatase (SAP) per 5 µl of PCR
product. The Exo/SAP added PCR products were incubated for
45 min at 37◦ C followed by denaturing at 80◦ C for 15 min in
the thermal cycler for deactivating unused exonuclease enzyme.
The Exo/SAP treated amplicons were mixed with 1 µl of BigDye

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Gene sequence diversity in chickpea

Terminator V3.1 (Applied Biosystems, California, USA), 2 µl of
5X sequencing dilution buffer and 3.2 µM of primer (forward and
reverse, separately) and the volume was made to 10 µl by adding
water. The sequencing PCR profile included an initial denaturation of 96◦ C for 30 s, followed by 60 cycles of 96◦ C for 10 s, 50◦ C
for 5 s, and 60◦ C for 4 min. The PCR products were stored at
4◦ C until further use. Before sequencing, the PCR products were
treated with 2.5 µl of 125 mM EDTA and 25 µl of absolute ethanol
and incubated for 15 min at room temperature to precipitate the
DNA. The plate containing the PCR product was centrifuged at
4000 rpm for 30 min at 4◦ C. The ethanol/ EDTA mix was poured
off by inverting the plate, without losing the pellet. To each well,
60 µl of 70% ethanol was added and again spun at 4000 rpm for
20 min at 4◦ C. The ethanol was poured off as earlier. The plate
was air-dried and 10 µl of HiDi formamide (Applied Biosystems,
California, USA) was added and the products were denatured
(94◦ C for 5 min, then immediately cooled to 4◦ C for 5 min)
and sequenced using an ABI3700/ABI3130 automated sequencer
(Applied Biosystems, California, USA).
ALLELE SEQUENCING AND SNP DETECTION

For allele sequencing, of candidate genes across the 300 genotypes of the reference set, PCR and purification were carried out
as described above. Sequencing was carried out at MACROGEN,
Korea using BigDye terminator cycle sequencing chemistry. Raw
sequences were used to obtain contigs by assembling the forward and reverse sequences of each genotype using DNA Baser V
2.9 tool and gene identities were confirmed using BLAST (blastn
and blastx). The sequences of each candidate gene were aligned
using CLUSTALW (http://www.ebi.ac.uk/Tools/clustalw2/index.
html). Multiple sequence alignment (MSA) files and fasta files
were further used for identifying equence related parameters such
as number of genotypes sequenced; length of sequences; number
of indels; indel frequency; number of SNPs and their types (transition or transversion); SNP frequency; nucleotide and haplotype
diversity and polymorphic information content (PIC) of SNPs
and haplotypes using an in-house tool developed at ICRISAT
called “DIVersity ESTimator” module (DIVEST) (Jayashree et al.,
2009). Further, in order to identify if any of the haplotypes
could be associated with the country of origin of the genotypes under study, NETWORK programme version 4.516 was
used to determine haplotype networks for each candidate gene
studied.

RESULTS
ISOLATION AND SEQUENCE ANALYSIS OF ABIOTIC STRESS
RESPONSIVE CANDIDATE GENES

An AKIN homolog was amplified using the gene specific primer
pair designed considering unigene sequence showing match with
Arabidopsis AKIN (SNF-1 related protein kinase). The approximate amplicon size of AKIN was ∼800 bp. Amplification of
an AMADH homolog yielded a product of ∼900 bp. The ABA
stress and ripening (ASR) gene was isolated using the heterologous primers derived from Medicago sequence AC152054. A
single amplicon of 700 bp was obtained for the chickpea genotypes used. A DREB2A homolog (also known as CAP2 gene)
and its promoter (CAP2 promoter) were amplified using a

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Table 1 | List of abiotic stress responsive genes and respective primers used for PCR amplification.
Putative function

Source sequence

SNF-1 related protein kinase
(AKIN)

Response to nutritional and
environmental stresses in plants

Chickpea ESTs

–

F: GTG GTT CAG GTG CAG ACT TG
R: TCA GAA AGT GCC CAT CAC GC

Aminoaldehyde dehydrogenase
(AMADH)

Osmotic stress, dehydration and
salt stress tolerance

Chickpea ESTs

–

F: TTG GAA GAA GGT TGC AGG CTA G
R: CCC ATT CTC CCA GTT CAC GG

Abscisic acid stress and
ripening (ASR)

Tolerance to drought and salt
stresses

Medicago

AC152054

F: GGG AAC TAA TCC TTT CCA AAC A
R: CTG CAG CAC CTA ACT CAC CA

CAP2 gene (DREB2A)

Regulates expression of water
stress-inducible genes

Chickpea

DQ321719

F: CGG CTT CCC TTC ATT CGA TCC A
R: AGG CAC AAC ACA AGA ATC CA

CAP2 promoter

Induce a set of abiotic
stress-related genes

Chickpea

–

F: TGT GCT TCA AGT TGC ACT CC
R: CGG GGT CCT TAT ATA CTG CAG A

Dehydrin (DHN)

Induced by environmental stress,
dehydration or low temperature

Chickpea ESTs

–

F: AAA GTG GTG TTG GGA TGA CC
R: TCC TCT CTC CCG AAT TCT TG

Dehydration responsive
element binding (DREB1)

Induced by dehydration and
high-salt stresses

Chickpea ESTs

–

F: CTT CAT TCG ATC CAG ATT CGG
R: AAC GCG AGT TTT CAG GCC CT

ERECTA (fragment 7F-5R)

Mediates plants’ responses to
disease and stress

Degenerate

–

F: GTG TAC AAA CCT TAA CAG CC
R:CCA GTT AAT TCG TTG TTT TC

ERECTA (fragment 8F-8R)

Mediates plants’ responses to
disease and stress

Degenerate

–

F: GGT CAG CTA CAG AAC ATA GCA
R: TCC ATT TTC CAT GTA GTC ATA A

Myb transcription factor

Response to biotic and abiotic
stresses

Chickpea ESTs

–

F: ATG CTA CTG CTG CCT ACA AG
R: ACC GCA GTA CAC TCC AAG AG

Sucrose synthase (SuSy)

Sugar metabolism pathway

Medicago

TC95820

F: GAT ACT GGC GGA CAG GTT GT
R: CAT CCT TTG CTA GGG GAA CA

Sucrose phosphate synthase
(SPS)

Induced by drought and mannitol

Medicago

BQ137986

F: TTT GGT CCA CGC GAT AAA TA
R: TGA ATT GAT ATC CTC CCA AGA

primer pair as described by Nayak et al. (2009). The approximate amplicon size of the CAP2 gene was 1000 bp while the
CAP2 promoter was ∼700 bp. A dehydrin homolog of chickpea
was amplified using a primer pair designed for known dehydrin gene using chickpea unigene. The approximate amplicon
size of dehydrin gene was ∼380 bp. A DREB1 (Dehydration
response element binding) homolog in chickpea was also amplified using a primer pair designed using unigene showing match
against DREB1 gene. The approximate amplicon size of the
DREB1 gene was ∼800 bp. About 4300 bp long ERECTA gene
fragments were isolated from eight chickpea genotypes using consensus primers. An ∼350 bp long MYB gene was amplified using
unigene sequence having match against Glycine max Myb transcription factor. For isolating the SuSy gene in chickpea, heterologous primers were designed from Medicago sequences TC95820
(homolog to SUS2 Pea) and AJ131964 (Medicago truncatula
SUS1 gene). An ∼1500 bp amplicon was obtained for TC95820derived sequences, while a 900 bp amplicon was obtained with
AJ131964- derived sequences. Heterologous primers designed
using Medicago sequence BQ137986 and CB893717 were used to
isolate SPS in chickpea. Amplification across eight genotypes in
chickpea yielded products of 400 bp in both cases (Table 2).

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GenBank/TC ID

Primer sequences (5 –3 )

Gene

SEQUENCE DIVERSITY ANALYSIS OF CANDIDATE GENES

Forward and reverse sequences for all 10 abiotic stress responsive candidate genes and the CAP2 gene promoter, were used for
contig construction. The number of genotypes for which good
quality sequences were obtained varied from 79 (ERECTA fragment obtained from 7f-5r primer pairs) to 236 genotypes (SPS
gene), out of the 300 genotypes. Diversity analysis of the candidate genes using the DIVersity ESTimator (DIVEST) tool is
presented in Table 3.
SNPs were manually inspected for possible sequencing errors
and only those SNPs with clear peaks were considered further (Figure 1A). Sequences for each gene were aligned using
CLUSTALW and positions of SNPs were identified (Figure 1B).
The highest number of SNPs (34) was obtained for the ASR gene,
amongst which 22 were transitions, 11 were transversions and one
was tri-allelic. Apart from SNPs, two indels were also detected.
The CAP2 gene was found to be conserved across all 227 genotypes with no SNPs and indels. In the case of CAP2 promoter,
one SNP was found (which was the same observed when eight
chickpea genotypes were sequenced as a pilot experiment). For
the ERECTA gene, two fragments obtained from 7f-5r and 8f8r primer pairs were sequenced. In total, 13 SNPs (9 transitions

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Gene sequence diversity in chickpea

Table 2 | Summary of abiotic stress responsive candidate genes showing match with previously reported accession/gene in other crop species.
Gene

Sequence length (bp)

Sequence similarity result

e-value

SNF-1 related protein kinase (AKIN)

772

SNF1-related protein kinase catalytic subunit alpha KIN10
[Arabidopsis thaliana] AKIN10

6.00E-41

Aminoaldehyde dehydrogenase (AMADH)

932

Betaine aldehyde dehydrogenase 1 [Arabidopsis thaliana]

2.00E-36

Abscisic acid stress and ripening (ASR)

680

(1) TC10668 similar to ASR protein homolog
(2) Medicago truncatula clone (AC126014.6)
(3) Prunus armeniaca (apricot) ASR (U93164.1)

2.80E-18
3.00E-29
0.003

CAP2 gene (DREB2A)

1000

DQ321719 (CAP2 gene Cicer arietinum)

0.00

CAP2 promoter

700

–

–

Dehydrin (DHN)

381

Dehydrin 1 [Cicer pinnatifidum]

2.00E-04

Dehydration responsive element binding (DREB1)

776

Dehydration responsive element binding protein [Cicer
arietinum]

2.00E-09

ERECTA

4300

LRR receptor-like serine/threonine-protein kinase ERECTA
[Medicago truncatula]

Myb transcription factor (MYB)

335

(1) MYB transcription factor MYB93 [Glycine max]
(2) Myb-like transcription factor family protein [Arabidopsis
thaliana]

2.00E-26
0.00

Sucrose phosphate synthase (SPS)

400

(1) M. truncatula (BQ137986) SPS like protein
(2) TC103232 homolog to Medicago sativa SPS (Q9AXK3)

7.90E-60
9.60E-21

Sucrose synthase (SuSy)

900

(1) M.truncatula SusS1 gene (AJ131964)
(2) Lotus japonicus genomic DNA clone (AP009336.1)
(3) Vigna radiata mRNA for SUSY (D10266.1)

2.00E-20
3.00E-18
3.00E-06

Table 3 | Estimation of sequence diversity in chickpea reference set/mini core collection using 10 abiotic stress responsive genes.
Candidate gene

AKIN #

AMADH #

ASR

CAP2

CAP2

DHN #

DREB1 #

promoter

ERECTA ERECTA
_7f_5r

_8f_8r

Myb#

SPS

SuSy

Genotypes with
successful sequences

208

209

193

227

137

198

191

79

147

200

236

230

Sequence length (bp)

772

932

621

367

629

381

776

921

1189

335

312

884

2

3

2

0

0

7

23

1

0

2

1

1/386.00

1/310.67

1/310.60

0

0

1/54.43

1/33.74

1/921.00

0

No. of SNPs

2

13

34*

0

1

7

14

13

20

6

3

1

Transition

2

6

22

0

0

5

8

9

10

1

2

1

1

0

No. of Indels
Indel frequency

Transversion

1/167.50 1/312.00

0
0

0

7

11

0

1

2

6

4

10

5

1/386.00

1/71.69

1/18.26

0

1/629.00

1/54.43

1/55.43

1/70.86

1/69.46

1/55.83

0.0004

0.002

0.0014

0

0

0.0022

0.0011

0.0029

0.0029

0.002

0.0011

0.0012

0.01

0.04

0.1

0

0.43

0.17

0.14

0.27

0.1

0.04

0.01

0.01

3

9

4

1

2

6

33

4

3

6

4

1

Haplotype diversity

0.019

0.326

0.833

0

0.438

0.426

0.879

0.372

0.324

0.256

0.034

0.035

PIC of haplotypes

0.019

0.324

0.829

0

0.436

0.424

0.874

0.367

0.322

0.255

0.034

0.033

SNP frequency
Nucleotide diversity (Pi)
Average PIC of SNP
No. of haplotypes

1/104.00 1/884.00

The sequence diversity was calculated using DIVEST tool (http://hpc.icrisat.cgiar.org/Pise/5.a/statistics_calculation/SNP_diversity_estimator.html) AKIN, SNF1 related
protein kinase; AMADH, Aminoaldehyde dehydrogenase; ASR, Abscisic acid stress and ripening gene; DHN, Dehydrin; DREB1, Dehydration responsive element
binding protein; Myb, Myb transcription factor; SPS, Sucrose synthase (SuSy) and sucrose phosphate synthase; # Gene was sequenced across 211 genotypes of
chickpea mini core collection; *One SNP is tri-allelic.

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Gene sequence diversity in chickpea

FIGURE 1 | (A) Comparison of sequence quality to confirm the true SNP using peak quality. The presence of SNP in DHN gene using sequence chromatogram
is highlighted. (B). Alignment of nucleotide sequences encoding DHN across various chickpea genotypes.

and 4 transversions) and one indel were obtained for ERECTA
7f-5r fragments while 20 SNPs (10 transitions and 10 transversions) were observed for ERECTA 8f-8r gene fragments. One indel
and 3 SNPs were observed across SPS gene sequences. The AKIN
gene showed the presence of two SNPs and two indels. A total
of 13 SNPs (6 transitions and 7 transversions) and 3 indels were
identified in the AMADH gene, while in the DHN gene 7 SNPs
(five transitions and two transversions) were identified among
198 sequences analyzed. For the MYB gene only 6 SNPs (one transition and five transversions) and 2 indels were found in 200 Myb
sequences under study. No nucleotide diversity was observed for
the CAP2 gene and promoter while in the case of AKIN it was
0.0004 and 0.0029 for both ERECTA fragments. The average polymorphic information content (PIC) value of SNPs ranged from
0 (CAP2 gene) to 0.43 (CAP2 promoter). Haplotype diversity
ranged from 0.019 (AKIN) to 0.879 (DREB1). Average (PIC) of
haplotypes values ranged from 0.019 (AKIN) to 0.874 (DREB1)
(Table 3).
HAPLOTYPE NETWORKS FOR CANDIDATE GENES

Based on the sequence information, haplotype networks were
drawn using the NETWORK program. The network figures show
the number of haplotypes observed for each gene and the SNP
position which separates one haplotype from the other. Network
diagrams can be drawn only with the presence of more than two
haplotype blocks. Haplotype frequency is depicted by circles, for

Frontiers in Plant Science | Plant Genetics and Genomics

example, the larger the haplotype circle, more genotypes are represented by that haplotype. The color code is given as per the
country of origin of the genotypes (Figures 2A–I). CAP2 and
SuSy gene represented only one haplotype with all the genotypes
sequenced while the CAP2 promoter had only one SNP, forming
two haplotype blocks. Hence haplotype network graphs could not
be drawn for CAP2 gene, its promoter and SuSy gene. The network analysis showed a linear relationship between haplotypes
for most of the genes except for transcription factors DREB1
and Myb, which showed network relationships between larger
numbers of haplotypes.
In this study, although we could find more than two haplotype
blocks in some of the candidate genes like AKIN, AMADH, ASR,
DHN, DREB, MYB, SPS, ERECTA (7f-5r), and ERECTA (8f-8r),
there was no clear distinction between the origin of the genotypes
and the haplotype information. Haplotype network analysis for
the AKIN gene reported three haplotypes, including one major
(H2) and two minor haplotypes (H1 and H3) (Figure 2A). The
AMADH gene showed the presence of nine haplotypes across the
reference set of which, one major haplotype (H9) is connected to
eight other haplotypes (Figure 2B). There were three minor haplotypes (H1, H2, and H4) derived from a major haplotype (H3) as
observed in ASR haplotype networks with SNPs ranging from one
to four (Figure 2C). DHN gene haplotype network indicated the
presence of six haplotypes, of which one major haplotype (H2)
was connected to three minor haplotypes (H1, H3, and H5) with

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Roorkiwal et al.

FIGURE 2 | Haplotype network of candidate genes developed based on
country of origin of genotypes of the chickpea reference set. (A) AKIN gene;
(B) AMADH gene; (C) ASR gene; (D) DHN gene; (E) DREB1 gene; (F) ERECTA
(7f-5r) gene; (G) ERECTA (8f-8r) gene; (H) MYB gene; (I) SPS gene; Each circle

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Gene sequence diversity in chickpea

represents a haplotype and is labeled accordingly. Colors in the circles represent
the countries of origin of chickpea genotypes. Circle size is in proportion to
frequency (the larger the circle the more genotypes in the haplotype). Numbers
in red represent the position of mutations separating the haplotypes.

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Roorkiwal et al.

one SNP and another haplotype (H6) with three SNPs which
was further connected to one minor haplotype (H4) with one
SNP (Figure 2D). The DREB1 gene exhibits a complex haplotype network owing to the presence of 33 different haplotypes,
which were connected to each other with 1–4 SNPs (Figure 2E).
Three major haplotypes (H3, H12, and H16) covers 17, 19, and
62 individuals respectively (Figure 2E). Similarly, in ERECTA- 7f5r gene fragment, one major haplotype (H1) defined by 10 SNPs
and two minor haplotypes (H3 and H4) defined by single SNP
were derived from major haplotype H2 (Figure 2F). In the case of
the other ERECTA fragment (8f-8r) two haplotypes (H1 and H2)
derived from H3 with 6 and 13 SNPs respectively (Figure 2G).
Haplotype network of Myb gene showed the presence of six haplotypes, of which two major haplotypes (H2 and H4) are connected
to four minor haplotypes with 1–2 SNPs (Figure 2H). SPS gene
haplotype network showed presence of three minor haplotypes
(H1, H2, and H4) derived from H3 with single nucleotide variation (Figure 2I). Accessions representing each haplotype were
color coded according to their country of origin. In the present
study, accessions in the major haplotypes were coming from Asia
and Middle East in all the genes. The haplotype for ERECTA 7f-5r
is unique to NE Africa. The network analysis showed linear relation between haplotypes in most of the genes except for DREB1
and Myb, which are transcription factors. It is also interesting to
note that these are the transcription factors which regulate many
downstream genes in plant system.

DISCUSSION
The present study was initiated with the objective of the identification of favorable alleles in abiotic stress responsive genes in
the chickpea reference set. These gene-based SNPs may be used
to identify the suitable allele of a gene that enable the plant to
survive in a stress environment. Due to lack of genome sequence
information of the chickpea genome until recently (Varshney
et al., 2013), identification of genes responsible for complex traits
like drought tolerance was a daunting task at the time of initiation of this study. Identification of candidate genes responsible
for drought tolerance was a part of an international collaborative project funded by the Generation Challenge Programme
(GCP) entitled “Allelic Diversity at Orthologous Candidate genes
(ADOC) in seven GCP crops”- one among them was chickpea.
An extensive literature survey was carried out to identify possible candidate genes responsible for abiotic stress tolerance, which
might have a consensus role in abiotic stress tolerance mechanism
in model crops and other legume crops.
Most of the genes analyzed here, have not been previously studied in chickpea. Therefore, systematic efforts by
using comparative genomics and bioinformatics approaches were
made to determine the corresponding gene sequences in chickpea. For instance, a DREB homolog of chickpea was isolated
by using sequence information available from chickpea. As
Medicago truncatula is the known taxonomic ally of chickpea, the
genomic information about Medicago was searched from different
databases including NCBI, TIGR, and Medicago sequence repository (www.medicago.org). Putative candidate genes in chickpea namely ASR, SuSy and SPS were isolated using respective
sequence information obtained from the Medicago candidate gene

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Gene sequence diversity in chickpea

sequences. In addition, the remaining abiotic stress responsive
genes (AKIN, AMADH, DHN, and MYB) were identified using a
sequence similarity approach against the homolog genes present
in model crops like Arabidopsis and Medicago. A large body
of evidence demonstrated that the Snf1-related protein kinases
(AKIN) serve as important regulators modulating fundamental
metabolic pathways in response to nutritional and environmental
stresses in yeast and mammalian cells (Hardie, 2007). To identify the AKIN homolog, chickpea ESTs were used for designing
the primers for PCR amplification in eight chickpea genotypes
based on sequence similarity with Arabidopsis thaliana (Table 2).
Researchers have isolated the AKIN homolog in various plant
species including Arabidopsis, wheat, rice, potato and tobacco
and have established their role in abiotic stress response (Coello
et al., 2012). The AKIN gene encodes two types of domains, catalytic kinase (highly conserved) domain and regulatory domain
(highly divergent). In the present study, the AKIN gene was found
to be mostly conserved except two unique alleles each reported
in specific genotype, which indicates that in the present study
we were able to amplify the conserved part of AKIN gene, i.e.,
catalytic kinase. Researchers can target the divergent regulatory
domain to identify the SNPs actively involved in abiotic stress
response. Similarly, a protective/curative role of the AMADH
gene in response to stress events caused by mechanical injury
was reported by Petrivalský et al. (2007) in pea seedlings. Since
AMADHs works on degradation of reactive metabolites that
show considerable toxicity, this enzyme was thought to serve
as a detoxification enzyme. An AMADH homolog was amplified using primers designed from chickpea ESTs and BLASTN
analysis confirmed its presence (Table 3). Over expression of
the AMADH genes from Arabidopsis have been shown to affect
stress responses (Missihoun et al., 2011). Based on various functional and characterization studies of the AMADH gene in rice,
Arabidopsis and other crop species (Skibbe et al., 2002; Tsuji
et al., 2003) makes this gene a suitable candidate for studying its
similar role in chickpea. In our study, AMADH showed the second highest number of SNPs (13) across the chickpea mini core
collection.
Expression of the ASR gene is regulated by water stress, salt
stress and plant hormone ABA. Over-expression of the ASR gene
in transgenic plants is known to induce water- and salt- stress tolerance (Kalifa et al., 2004). Although ASR gene function is not
published in the case of Medicago, ASR-like sequences that were
similar to some of the reported ASR sequences in other crops were
used to design primers and amplified in chickpea. The sequence
diversity across chickpea genotypes (193 sequences) showed 34
SNPs and two indels, highest among the candidate genes studied in the present study. The nucleotide diversity was found to be
0.0014 while haplotype diversity was 0.833. Cortés et al. (2012b)
also analyzed the diversity of two ASR genes in a set of wild
and cultivated beans and found two contrasting diversity patterns, most particularly for wild beans. A similar study in rice
was carried out, where the polymorphism of four members of
the ASR gene family was studied in a worldwide collection of 204
accessions of Oryza sativa and 14 accessions of wild relatives (O.
rufipogon and O. nivara). This study provided a thorough description of the organization of the ASR family, and the nucleotide and

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Roorkiwal et al.

haplotype diversity of four ASR genes in O. sativa (Philippe et al.,
2010).
The chickpea CAP2 gene (a homolog of DREB2A) and its
promoter, known to enhance tolerance to dehydration and salt
stress, were isolated, characterized and expression studies were
carried out in transgenic tobacco (Shukla et al., 2006). The
sequence information was used to design nested primers in
order to isolate the full-length CAP2 gene during the present
study. The study also showed extreme conservation of the AP2
domain of the DREB2 genes across five species studied (Nayak
et al., 2009). DREB transcription factors bind to the dehydration responsive element (DRE) of the genes at the promoter
region and regulate the expression of downstream genes. The
DRE containing core sequence A/GCCGAC was identified as a
cis-acting promoter element, which regulates gene expression in
response to drought, high salinity and cold stresses in Arabidopsis
(Yamaguchi-Shinozaki and Shinozaki, 1994). The CAP2 gene and
its promoter were sequenced in 300 diverse chickpea genotypes.
The occurrence of a SNP within a regulatory region, accounting for the loss of function of a seed shattering gene has been
already shown in rice, which indicates that single sequence variants can cause major effects on the function of gene(s) (Konishi
et al., 2006). Conservation of the AP2 domain of the DREB2A
gene was observed, not only within chickpea sequences, but also
across other crop species; common bean, rice, sorghum and barley (Nayak et al., 2009). DREB2A diversity analysis in common
bean (Cortés et al., 2012a) revealed a very high diversity level
compared to DREB2B in these other species, indicative of adaptive
selection and population expansion.
The DHNs are one of the several proteins that have been
specifically associated with qualitative and quantitative changes
in cold hardiness (Close, 1996). Arabidopsis plants engineered for
DHN over-expression, showed improved survival when exposed
to low temperature (Puhakainen et al., 2004). Similarly, transgenic tobaccos with increased level of expression of a citrus
dehydrin protein have shown tolerance to low temperature (Hara
et al., 2003) making DHN a suitable candidate gene for study
in chickpea. Researchers have distinguished five different DHN
genes in silico, which could be grouped into two types-K2 and
SKn. Three of the dehydrin genes reported several sequence
variants which differ by multiple or single amino acid substitutions (Velasco-Conde et al., 2012). The role of ERECTA genes
in drought tolerance pertains to their involvement in stomatal
density and evapotranspiration (Shpak et al., 2004; Masle et al.,
2005). Two fragments of ERECTA genes were isolated in the
present study. In chickpea, a total of 33 SNPs (13 from fragment
obtained from ERECTA-7f-5r and 20 from fragment obtained
from ERECTA-8f-8r) making 7 haplotypes (4 in ERECTA-7f-5r
and 3 in ERECTA-8f-8r) were observed. Nucleotide diversity was
found to be 0.0029 which was high compared to all other candidate genes under study. The sequence diversity studies across the
reference set of chickpea, provides the insights regarding existing
haplotypes, which could be involved in drought tolerance mechanism. The role of plant Myb-proteins has been well characterized
by using different genetic approaches. In most of the cases, the
Myb domain binds to a specific DNA sequence (C/TAACG/TG)
to facilitate transcriptional activation (Biedenkapp et al., 1988).

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Gene sequence diversity in chickpea

A rice R2R3-type MYB transcription factor gene, JAmyb, whose
overexpression causes tolerance to high salinity has been identified (Yokotani et al., 2013).
The SuSy and SPS genes encode for the enzymes involved in
sugar metabolism and are known to be up-regulated in dehydration stress. The SuSy gene in chickpea is also associated with
increased seed size (Kumar and Turner, 2009). A partial SuSy
gene was isolated here, and sequencing discovered only 1 SNP
across the chickpea reference set. The SuSy gene is a candidate
gene for drought tolerance in many plant species (Gonzalez et al.,
1995; Baud et al., 2004), and the SPS gene was found to be
involved with drought tolerance in maize (Abdel-latif, 2007) and
wheat (Fresneau et al., 2007). An SPS homolog was identified in
chickpea in the present study. Diversity analysis of this gene on
the reference set of chickpea showed the presence of three SNPs
and one indel represented as four haplotypes across 235 chickpea genotypes. This observation indicates the conservation of
this gene across chickpea genotypes. Studies on sequence diversity on the SPS gene are limited to date. Sequence diversity of
an SPS gene was studied for two cultivars of sugarcane and 10
SNPs were identified in a 400 bp sequenced region. These SNPs
were screened on a mapping population derived from the two
cultivars. The SNP frequency did not vary in the two bulked
DNA samples, suggesting that SNPs from this SPS gene family
are not associated with variation in sucrose content. Estimation
of genetic diversity serves many purposes concerning breeder’s
interest, like identification of distinct genetic groups for retention
in germplasm, identification of genes responsible for phenotypic variation accrued during domestication (Ross-Ibarra et al.,
2007) and inference of crop evolution. Allelic diversity studied
through NETWORK indicated the distribution of different alleles
across the globe based on the origin of the accessions. For some
genes (ex: ERECTA 7F-5r), haplotypes identified were coming
from particular geographic area (ex: H1 from NE Africa). Such
haplotypes indicate a historical constraint as a result of selection, domestication or adaptation. In rice, a haplotype study of
three genes revealed the difference in domestication pattern of
cultivated and wild rice cultivars (Londo et al., 2006; Kovach
et al., 2007). In the present study, linear haplotype networks
were found in all genes except for transcription factors DREB1
and Myb. Diversity of transcription factors at a sequence and
functional level may affect downstream genes and their expression. Knowledge about genetic diversity and relationships within
the diverse germplasm is also useful for breeders as it facilitates
their decisions on the selection of the parents for hybridization
when widening the genetic basis of breeding programs. Molecular
variation in the germplasm can help in the selection of superior genotypes for the generation of new varieties for several
agronomic traits. A total of 114 SNPs and 41 indels have been
identified in these abiotic stress responsive genes across the chickpea reference set. These SNPs and indels were used for diversity
estimation using DIVersity ESTimator (DIVEST). Among the 114
SNPs detected, 66 SNPs regions were transitions, whereas the
other 49 were transversions, and one SNP was reported tri-allelic.
The nucleotide diversity across the chickpea mini core collection ranged from 0.0004 to 0.0022 with overall mean diversity of
0.0015. The possibilities of association mapping can be explored

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Roorkiwal et al.

further by linking sequence diversity with the phenotype diversity in order to identify favorable alleles or haplotypes conferring
drought tolerance in chickpea.

ACKNOWLEDGMENTS
This study was funded by grants from CGIAR Generation
Challenge Programme (GCP), Mexico and Department of
Biotechnology (DBT), Government of India. Authors are thankful to Dr. Julie Hoffer for her comments/suggestions to improve
the MS. This work has been undertaken as part of the CGIAR
Research Program on Grain Legumes. ICRISAT is a member of
CGIAR Consortium. Thanks are also due to several colleagues at
ICRISAT, GGSIPU and partners in collaborating centers.

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Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Received: 10 January 2014; accepted: 15 May 2014; published online: 05 June 2014.
Citation: Roorkiwal M, Nayak SN, Thudi M, Upadhyaya HD, Brunel D, Mournet P,
This D, Sharma PC and Varshney RK (2014) Allele diversity for abiotic stress responsive candidate genes in chickpea reference set using gene based SNP markers. Front.
Plant Sci. 5:248. doi: 10.3389/fpls.2014.00248
This article was submitted to Plant Genetics and Genomics, a section of the journal
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