Gene pyramiding and omics approaches for stress tolerance in leguminous plants - Legumes Under Environmental Stress: Yield, Improvement and Adaptations - page 276

plant (Dita et al., 2006). Among the legumes, TILLING's
capacity for assortment of mutants is suited to L. japoni-
cus , M. truncatula, G. max and peanuts (Perry et al., 2003).
The tobacco retrotransposon Tnt1 has been used effec-
tively for insertional mutagenesis in M. truncatula ,
showing its value as a tool for functional genomics
(Tadege et al., 2005). For use in reverse genetics, TILLING
populations for Medicago (12,000 M2 plants) and Lotus
(4904 M2 lines) were reported (Perry et al., 2009; Rogers
et al., 2009). Apart from these model plants, TILLING
populations for peanuts (10,000 lines), chickpea
(~3500) and common bean (3000 M3 lines) have been
reported to be produced for allergenicity, drought toler-
ance and root nodulation respectively (Porch et al.,
2009; Tadege et al., 2009; Kudapa et al., 2013).

liquid chromatography tandem mass spectrometry, gas
chromatography-mass spectrometry (Huhman & Sumner,
2002) and nuclear magnetic resonance (NMR) (Bligny &
Douce, 2001).
Even though complete metabolomic studies are not
easy, a number of targeted investigations have been
carried out to identify the participation of subsets of
metabolites in a variety of stresses in legumes (He &
Dixon, 2000). Until now there have been comparatively
few studies of legume seeds at the metabolomic level
(Thompson et al., 2009). Bell and coworkers (2001)
employed metabolomics in a M. truncatula cell suspension
to find out reactions to different stimuli. Metabolomics
along with transgenomics has helped in crop improve-
ment by increasing the intrinsic stress resistance levels
in legume crops (Wu & Van Etten, 2004). Soluble metab-
olites of the legume L. japonicus were profiled by Sanchez
and coworkers (2008) using gas chromatography/mass
spectrometry. This examination revealed metabolic
adaptations of the plants that tolerated salt stress. The
modification in metabolic phenotype was without doubt
concurrent with the rising salt concentration. Those
metabolic alterations established a qualitative resem-
blance to the observed changes in patterns of gene
expression of the legume. A comparison of the seed
metabolome of pea lines possessing and deficient in pea
albumin 2 (PA2) was carried out by Vigeolas et al. (2008).
Pea albumin 2 is a chief reserve protein produced by
introgression of a naturally occurring PA2 locus deletion
into a standard genetic background. It was found that
the lack of this protein was related to the dissimilarity
in amino acid and polyamine contents in the seed. This
was attributed in some measure to reduction in the
actions of two enzymes of polyamine synthesis, i.e.
spermidine synthase and arginine decarboxylase. A case
study of the metabolic responses to long-term salt stress
in the model legume L. japonicus was conducted by
Sanchez et al. (2010). The study suggested that the major
metabolic alterations of legumes in salt stress depend
upon uncontrolled environmental variables. Silvente
and coworkers (2012) studied the metabolite modifica-
tions in response to water stress in drought-sensitive
(DM50048) and drought-tolerant (NA5009RG) geno-
types of soybean. Metabolite adjustments in relation to
physiological responses in the presence of short-term
water stress were elucidated on physiology of both
genotypes using 1 H NMR. These two genotypes showed
major differences in physiological responses, which led

16.2.2.5 Metabolomics
Proteomics and transcriptomics are significant areas in
decoding a biological pathway, but these techniques are
still not enough without the study of cell metabolites
because nearly all biological processes are eventually
controlled by cell metabolites. Therefore to understand
any process in more detail, it is important to study the
metabolome of the organism. The term metabolome
encompasses all the metabolites in a biological cell,
tissue, organ or organism, which are the end products of
cellular processes (Jordan et al., 2009). The metabolome
can be regarded as the final stage of gene expression,
one that describes the biochemical phenotype of a cell
or tissue (Sumner et al., 2003). Metabolomics is the
study of the distinctive chemical fingerprints that are
residual of definite cellular processes. Therefore, when
transcriptomics and proteomics do not provide a
complete picture of what might be happening in a cell,
metabolic profiling can provide a snapshot of the func-
tioning of that cell (Daviss, 2005). A full survey of the
biochemical state of an organism is made possible by
quantitative and qualitative study of great numbers of
cellular metabolites. Thus gene function of that organism
can be screened and evaluated by metabolomics (Fiehn
et al., 2000).
Several techniques are needed for a complete exam-
ination of the metabolite profile (Hall et al., 2002).
They include thin layer chromatography (Tweeddale
et al., 1998), high-performance liquid chromatography
(HPLC) with ultraviolet and photodiode array detec-
tion (Fraser et al., 2000), infrared spectroscopy (Oliver
et al., 1998), liquid chromatography-mass spectrometry,