Salt stress and leguminous crops: Present status and prospects - Legumes Under Environmental Stress: Yield, Improvement and Adaptations - page 39

to understand and dissect the cascades of events that are
involved in salt stress responses and mechanisms. In
addition, many studies have shown that environmental
stresses that cause cellular dehydration, like salt, water
and cold stress, often lead to similar changes in plant
gene expression and metabolism, and strong cross-talk
can be seen in their signalling pathways. Therefore,
more comprehensive approaches, including quantitative
and qualitative analysis of gene expression products, are
necessary for better analysis at the transcriptome, pro-
teome and metabolome levels (Rossignol et al., 2006).
The omic technologies such as transcriptomics, pro-
teomics and metabolomics have generated major
interest among researchers and also opened up new
perspectives in studying stress physiology of many
plants (Langridge & Fleury, 2011). The 'omic' technol-
ogies also generate huge amounts of information, which
have enriched the field of bioinformatics, with thou-
sands of new algorithms and new software published
every year. The development of these tools has allowed
the inference of the causal relationship among the ana-
lysed elements. Another significant technological
development has been the improvement in data storage
and computational capabilities associated with the
acquisition and processing of large datasets. In addition,
numerous web and software platforms intended to
share, assimilate and visualize in a biological context the
vast amount of data have been developed.
Numerous large germplasm collections have been
founded, which contain large amounts of genetic diver-
sity, including landraces and varieties as well as wild
relatives and modern varieties no longer in use. Legumes
have large variations in the size of their nuclear
genomes, ranging from 370 million base pair (Mbp) in
Lablab niger to 13,000 Mbp in Vicia faba (Aramuganathan
& Earle, 1991a,b). Black gram, mung bean, common
bean, lima bean, tepary bean and cowpea have the
smallest genomes (574 to 647 Mbp); pigeon pea (784,
882 Mbp) and chickpea (738 Mbp) have slightly larger
genomes; soybean has a relatively large genome (1115
Mbp); while pea and lentil (4063 to 4397 Mbp) and
broad bean (12,603 Mbp) have massive genomes.
Genomic resources include: markers; expressed sequence
tag (EST) and bacterial artificial chromosome (BAC)
libraries; genetic, cytogenetic and physical maps; and
identification of quantitative trait loci (QTL) associated
with beneficial traits; all of these resources are used in
applied breeding. In recent years, tremendous progress

has been made towards developing genetic markers,
especially short sequence repeats (SSRs) and single
nucleotide polymorphisms (SNPs), and/or construction
of high-density genetic linkage maps in chickpea,
groundnut and pigeon pea (Varshney et al., 2009).
Molecular markers have enabled researchers to more
rapidly and precisely characterize genetic diversity,
identify trait-based genetically diverse germplasm,
target genes underlying key agronomic traits, and
develop molecular assays that are both relevant and of
appropriate scale for breeding applications. More impor-
tantly, high-throughput and cost-effective genotyping
platforms, combined with automation in phenotyping
methodologies, will encourage the application of
genomic tools into breeding programmes, and thus
usher in an era of genomics-enabled molecular breeding
in legumes (Varshney et al., 2009).
Next generation sequencing (NGS) permits the mass
sequencing of genomes, which is producing a vast array
of genomic information. NGS data can be further anal-
ysed by bioinformatics tools enabling the discovery of
new genes and regulatory sequences and their posi-
tions, and making available large collections of molecular
markers. Genome-wide expression studies provide
breeders with a better understanding of the molecular
basis of complex traits as they usually reveal their multi-
gene nature and the importance of environmental
influences. Genome approaches also include targeting
induced local lesions in genomes (TILLING) and
EcoTILLING, which have potential to screen mutants
and germplasm collections for allelic variants of target
genes aiding in their functional analysis.
Medicago truncatula and Lotus japonicus have emerged
as models for plant genomic research in legumes.
Scientists now study these species to investigate a range
of questions from disease resistance to environmental
stress tolerance and from bacterial and fungal symbiosis
to complex secondary metabolism. However, both are
temperate legumes. For tropical legumes, soybean has
emerged as a model genome. Genomes of several
legumes have been sequenced and some species are cur-
rently the subject of independent large-scale sequencing
projects (Table 2.2). In addition, large-scale transcrip-
tomics, proteomics, metabolomics, phenomics and
bioinformatics resources and reverse genetic tools have
been developed. The characterization of these three
legume genomes ( M. truncatula, L. japonicus and soybean)
will undoubtedly enhance ongoing comparative genomic