**3. Genetic regulation mechanisms for tolerance to water stress**

#### **3.1. Drought tolerance**

#### *3.1.1. Genetic and QTL structure of morpho-physiological performance*

The application of QTL helps in identification of chromosomal regions, detecting phenotypic variation associated with drought-resistance traits and to determine the desirable alleles at these QLs for marker-assisted breeding. Progress towards the identification of droughtrelated QTLs is needed [118], only a few QTLs have been reported for drought (**Table 2**). Du et al. [128] identified 19 QTLs associated with seed yield under normal and water-limited conditions and 10 QTLs associated with drought susceptibility index (DSI) in soybean. To develop drought-tolerant varieties, the role of secondary traits associated with yield stability has been accelerated. In crops, under water deficit condition, several secondary traits i.e. early seedling vigor [129], canopy wilting [119, 130], root system architecture (RSA) [117, 131, 132], canopy temperature depression [133], carbon isotope discrimination [134, 135], alterations in photosynthesis [136, 137], and nitrogen fixation [138–141] have been reported.

In soybean, RSAs, slow canopy wilting and biological nitrogen fixation are promising secondary traits under drought [112]. Under water deficit conditions, a simulation analysis model depicted that slow wilting can improve soybean yield >75% while nitrogen fixation up to 85% [142]. In soybean, less information is available on QTL mapping of drought-associated traits and yield [128, 143], fibrous roots [144] and water-use efficiency (WUE) [123, 125, 126] under water-limited conditions. Several studies have been conducted on QTL mapping for RSA traits in major cereals crops with little information in leguminous crops, especially soybean [145–147]. Five QTLs were identified on chromosomes 1, 3, 4, 8, and 20 related with fibrous rooting systems in RIL population of soybean derived from a cross between Benning (low fibrous root) and PI 416937 (extensive fibrous root) [144]. These QTLs were detected by using 240 F6 derived recombinant inbred lines (RILs) under rain-fed conditions for 2 years (2001 and 2009). The parent PI 416937 (extensive fibrous root system) contributed favourable alleles for four QTLs, while one QTL had donor alleles from Benning. Moreover, a total of four QTLs related with root surface area and distribution (based on root length and thickness) were identified in an inter-specific mapping population (*Glycine max* × *Glycine soja*). Two QTLs on Chr 6 had favourable donor alleles from the wild parent, PI 407162 (*G. soja*) with R2 value of >10%. As a result, plants enhanced their ability to form fibrous roots. Manavalan et al. [148] identified one QTL cluster associated with root length and lateral root number in 251 BC2F5 backcross inbred lines through linkage mapping with favourable alleles from Dunbar (**Table 2**).

**Trait QTL Chro. Marker** *R***<sup>2</sup> Population Ref.** Canopy wilting *Gm02-1* 2 ss107913715 0.06–0.12 KJ, BP [119]

Leaf wilting *Gm09* 9 Sat044 0.17 Jackson ×KS4895 [122] Canopy wilting *Gm11* 11 ss107913507 0.14–0.39 KJ, KP, AP [119]

Yield *Gm06* 6 Satt205-satt489 0.7 Minsoy ×Noir 1 [123]

Yield and wilting *Gm13* 13 Sat\_375 – Hutcheson ×

*–* – A063-1 0.8

*Gm12* 12 A089-1 8.7 *Gm16* 16 cr497-1 13.2 *Gm16* 16 K375-1 7.5 *Gm4* 4 A063-1 5

*Gm19* 19 Satt561 0.18 *Gm13* 13 BARC-014657-01608 0.24 *Gm17* 17 BARC-057467-14,765 0.12

**Table 2.** A list of reported QTLs in soybean associated with drought tolerance.

*Gm13-1* 13 Sat\_074 – *Gm17* 17 Satt226 –

*qSW-Gm17/ Gm17–1*

Water use efficiency

Nitrogen fixation (shoot ureide)

KN = Kefeng1 × Nannong1138-2.

*Gm02-2* 2 ss107912946/satt296 0.06–0.18 AP [119, 120] *Gm02-3* 2 Satt296 0.06–0.19 BP, AP [119] *qSW-Gm04* 4 Satt646 0.09 BP [120] *Gm05* 5 ss107913925/satt276 0.04–0.16 KJ [119, 120] *Gm08* 8 Satt177 0.05–0.15 KJ, KN [119, 121]

*qSW-Gm12* 12 Satt302 0.27 BP [120] *Gm13* 13 Satt362 0.16 KJ [121] *Gm14* 14 ss107913401 0.08–0.12 KJ,AP [119, 121]

*Gm17-2* 17 ss107913610 0.09–0.10 KJ, KP [119] *qSW-Gm19* 19 ss107924069 0.11–0.29 KJ, KP, BP [119]

*Gm19* 19 A489H 0.14 S-100 × Tokyo [125]

*Gm18* 18 B031-1 8.5 Young ×PI416937 [126]

*Gm09* 9 BARC-060299-16,598 0.16 KS4895 × Jackson [127]

KJ = KS4895 × Jackson; BP = Benning × PI 416937; AP = A5959 × PI 416937; KP = KS4895 × PI 424140;

17 ss107929993 0.06–0.22 KJ,AP, BP [119–121]

PI471938,

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43

[124]

Slow canopy wilting is a key factor to screen soybean germplasm under water-limited conditions [121]. A total of 13 QTLs associated with slow wilting were detected using five bi-parental populations under water-limited conditions, with phenotypic variation (R2 0.04–0.29). Eleven out of 13 QTLs had favourable alleles from PI 416937 and Jackson [119–121]. The major QTL associated with slow wilting was mapped on LG K with 17% phenotypic variation [122]. To validate QTL data from different mapping population on same linkage map, 'Meta-QTL analysis' has been proposed [149, 150]. In soybean, Meta-QTL analysis was used to refine the confidence interval of eight QTLs using mapping results from five bi-parental population However, these QTLs are complex, unstable and quantitative nature, so breeders find difficulties to utilize them [151]. Considering this problem, confirmation of QTL should be performed by using more advanced progeny or near isogenic lines (BCnF2 ).

Studies on QTL mapping associated with biological-nitrogen fixation are very few in plants including soybean. Three QTLs for nodule number (LGs B1, E) were identified using the composite interval mapping and explained 13% phenotypic variation [152]. Two QTLs for shoot ureide were detected on Chrs. 9 and 19, and two QTLs associated with shoot nitrogen concentration were mapped on Chrs. 13 and 17 under water stress. These QTLs explained phenotypic variation ranging from 0.11 to 0.31 (**Table 2**) [127]. Jackson contributed favourable alleles for shoot ureide concentration on Gm 19 and Gm 13 while other two on Gm 09 and Gm17 have favourable alleles from KS4895. Under well-watered conditions, a number of QTLs associated with shoot ureide and nitrogen concentrations were reported. However, not a single QTL was detected under both conditions (stress and control) illustrating that soybean shows diverse mechanisms for regulation of N<sup>2</sup> -fixation under well-watered and drought conditions [127].


KJ = KS4895 × Jackson; BP = Benning × PI 416937; AP = A5959 × PI 416937; KP = KS4895 × PI 424140; KN = Kefeng1 × Nannong1138-2.

**Table 2.** A list of reported QTLs in soybean associated with drought tolerance.

In soybean, RSAs, slow canopy wilting and biological nitrogen fixation are promising secondary traits under drought [112]. Under water deficit conditions, a simulation analysis model depicted that slow wilting can improve soybean yield >75% while nitrogen fixation up to 85% [142]. In soybean, less information is available on QTL mapping of drought-associated traits and yield [128, 143], fibrous roots [144] and water-use efficiency (WUE) [123, 125, 126] under water-limited conditions. Several studies have been conducted on QTL mapping for RSA traits in major cereals crops with little information in leguminous crops, especially soybean [145–147]. Five QTLs were identified on chromosomes 1, 3, 4, 8, and 20 related with fibrous rooting systems in RIL population of soybean derived from a cross between Benning (low fibrous root) and PI 416937 (extensive fibrous root) [144]. These QTLs were detected by using 240 F6 derived recombinant inbred lines (RILs) under rain-fed conditions for 2 years (2001 and 2009). The parent PI 416937 (extensive fibrous root system) contributed favourable alleles for four QTLs, while one QTL had donor alleles from Benning. Moreover, a total of four QTLs related with root surface area and distribution (based on root length and thickness) were identified in an inter-specific mapping population (*Glycine max* × *Glycine soja*). Two QTLs on Chr 6 had favourable donor alleles from the wild parent, PI 407162 (*G. soja*) with R2 value of >10%. As a result, plants enhanced their ability to form fibrous roots. Manavalan et al. [148] identified one QTL cluster associated with root length and lateral root number in 251 BC2F5 backcross inbred lines through linkage mapping with favourable alleles from Dunbar (**Table 2**). Slow canopy wilting is a key factor to screen soybean germplasm under water-limited conditions [121]. A total of 13 QTLs associated with slow wilting were detected using five bi-parental populations under water-limited conditions, with phenotypic variation (R2 0.04–0.29). Eleven out of 13 QTLs had favourable alleles from PI 416937 and Jackson [119–121]. The major QTL associated with slow wilting was mapped on LG K with 17% phenotypic variation [122]. To validate QTL data from different mapping population on same linkage map, 'Meta-QTL analysis' has been proposed [149, 150]. In soybean, Meta-QTL analysis was used to refine the confidence interval of eight QTLs using mapping results from five bi-parental population However, these QTLs are complex, unstable and quantitative nature, so breeders find difficulties to utilize them [151]. Considering this problem, confirmation of QTL should be

42 Plant, Abiotic Stress and Responses to Climate Change

performed by using more advanced progeny or near isogenic lines (BCnF2

soybean shows diverse mechanisms for regulation of N<sup>2</sup>

drought conditions [127].

Studies on QTL mapping associated with biological-nitrogen fixation are very few in plants including soybean. Three QTLs for nodule number (LGs B1, E) were identified using the composite interval mapping and explained 13% phenotypic variation [152]. Two QTLs for shoot ureide were detected on Chrs. 9 and 19, and two QTLs associated with shoot nitrogen concentration were mapped on Chrs. 13 and 17 under water stress. These QTLs explained phenotypic variation ranging from 0.11 to 0.31 (**Table 2**) [127]. Jackson contributed favourable alleles for shoot ureide concentration on Gm 19 and Gm 13 while other two on Gm 09 and Gm17 have favourable alleles from KS4895. Under well-watered conditions, a number of QTLs associated with shoot ureide and nitrogen concentrations were reported. However, not a single QTL was detected under both conditions (stress and control) illustrating that

).


#### *3.1.2. Identification of important genes for drought tolerance*

Drought stress-responsive genes are categorized as effectors and regulatory genes [153]. Effectors include gene encoding protein such as LEA proteins, osmolyte biosynthesis (osmotin), aquaporins, chaperons, antioxidants and enzymes involved in different metabolic pathway. Regulatory genes encoding product such as receptors, calmodulin-binding proteins, kinases, phosphatases and transcription factors are involved in signal transduction and gene expression [153]. A number of plant TFs such as ethylene-responsive factor, WRKY, MYB, basic leucine zipper domain (bZIP) and NAC are involved in ABA signalling under drought stress, while dehydration responsible element binding (DREB) protein, are involved in ABA-independent pathway [154–156]. Major families of TF genes expressed in response to drought stress in plants are summarized in **Table 3**.

in GmNAC29 promoter and suppressed gene expression of GmNAC29 led to increased tolerance to abiotic stress [172]. In soybean, novel candidates of WRKY genes were detected, which provided the unique function of WRKY transcription factors under water deficit conditions [173]. Another gene family, Homeodomain-leucine zipper (HD-Zip) comprised of 140 HD-Zip genes (http://planttfdb.cbi.pku.edu.cn/family.php?fam=HD-ZIP) were detected under drought and salt stress. Out of 140, 59 are coding genes while 20 paralogous genes exhibited differential expression under drought and saline environment [174]. In soybean, overexpression of GmDREB3 also

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45

In recent years, the advent of molecular marker technologies has opened up new opportunities for QTL analyses, fine mapping and cloning of genes for water stress tolerance. The genetic basis of drought and flooding tolerance has been studied by evaluating different component traits in drought and flood-tolerant soybean. Both drought and flooding tolerance are quantitatively inherited and controlled by several genetic loci. Consequently, a large number

The analysis of quantitative trait loci (QTLs) for water-logging tolerance in soybean is usually challenging. However, several studies have been done on QTLs associated to flooding tolerance, focused on injury score and tolerance index in soybean [91, 176–179, 182]. For instance, a single QTL located on Chr. 18 (Sat\_064) was identified using 208 lines of two recombinant inbred (RI) populations, for soybean growth and grain yields under water-logging conditions [176].

**Trait QTL Chro. Marker Population Ref.** Grain yield *Gm18* 18 Sat\_064 Archer × Minsoy, Archer × Noir I [176] Injury score, tolerance index *Gm5, Gm13* 5, 13 Satt385, Satt269 A5403 × Archer, P9641 × Archer [177] Flooding tolerance *ft1* 6 Satt100 Misuzudaizu × Gong 503 [178] Seed germination *Sft1, Sft2* 12, 8 Sat\_175, Satt 187 Peking × Tamahomare [91]

*Sft3, Sft4* 4, 2 Satt 338, Sat\_279

*FTS-13* 13 Sct\_033, BARC-

*FTS-11* 11 BARC-016279-

*Wt1,wt2* 19 Satt229-Satt527

**Table 4.** A summary of QTL mapping studies for flood tolerance traits in soybean.

024569-4982

Satt527-Sat\_286

*Qhti-12-1* 12 Satt052-Satt302 Iyodaizu × Tachinagaha [181]

02316

PI 408105A × S99-2281 [179]

Su88-M21 × Xinyixiaoheidou [180]

enhances tolerance drought tolerance in response to accumulation of proline [175].

of QTLs related to flooding tolerance are summarized in **Table 4**.

**3.2. Flooding tolerance**

*3.2.1. QTL mapping*

Flooding toleranceand/or resistance to *P. sojae*

Joint waterlogging tolerance

Root length development/ Root surface area

index

In the soybean genome, 5035 TFs models were identified based on in-silico annotation [170]. Among all TFs, the WRKY transcription factor is the largest family in plants. A total of 233 WRKY members have been identified in soybean (http://planttfdb.cbi.pku.edu.cn/family.php? fam=WRKY) [171]. Identification of two WRKY genes (GmWRKY21 and GmWRKY54) and their role in enhancing tolerance to drought, salt and cold has been studied in *Arabidopsis* [156]. Moreover, the involvement of GmWRKY27 has been characterized under drought and salt stress. Overexpression of GmWRKY27 RNAi and GmWRKY27 in soybeans results in increased tolerance and hypersensitivity to drought and salt stress, respectively. In the same study, the association of GmWRKY27 with GmMYB174 was observed, which binds to neighbouring cis-elements


**Table 3.** Major families of TF genes expressed in response to drought stress in plants.

in GmNAC29 promoter and suppressed gene expression of GmNAC29 led to increased tolerance to abiotic stress [172]. In soybean, novel candidates of WRKY genes were detected, which provided the unique function of WRKY transcription factors under water deficit conditions [173].

Another gene family, Homeodomain-leucine zipper (HD-Zip) comprised of 140 HD-Zip genes (http://planttfdb.cbi.pku.edu.cn/family.php?fam=HD-ZIP) were detected under drought and salt stress. Out of 140, 59 are coding genes while 20 paralogous genes exhibited differential expression under drought and saline environment [174]. In soybean, overexpression of GmDREB3 also enhances tolerance drought tolerance in response to accumulation of proline [175].

#### **3.2. Flooding tolerance**

#### *3.2.1. QTL mapping*

*3.1.2. Identification of important genes for drought tolerance*

44 Plant, Abiotic Stress and Responses to Climate Change

Drought stress-responsive genes are categorized as effectors and regulatory genes [153]. Effectors include gene encoding protein such as LEA proteins, osmolyte biosynthesis (osmotin), aquaporins, chaperons, antioxidants and enzymes involved in different metabolic pathway. Regulatory genes encoding product such as receptors, calmodulin-binding proteins, kinases, phosphatases and transcription factors are involved in signal transduction and gene expression [153]. A number of plant TFs such as ethylene-responsive factor, WRKY, MYB, basic leucine zipper domain (bZIP) and NAC are involved in ABA signalling under drought stress, while dehydration responsible element binding (DREB) protein, are involved in ABA-independent pathway [154–156]. Major families of TF genes expressed in response to drought stress in plants are summarized in **Table 3**. In the soybean genome, 5035 TFs models were identified based on in-silico annotation [170]. Among all TFs, the WRKY transcription factor is the largest family in plants. A total of 233 WRKY members have been identified in soybean (http://planttfdb.cbi.pku.edu.cn/family.php? fam=WRKY) [171]. Identification of two WRKY genes (GmWRKY21 and GmWRKY54) and their role in enhancing tolerance to drought, salt and cold has been studied in *Arabidopsis* [156]. Moreover, the involvement of GmWRKY27 has been characterized under drought and salt stress. Overexpression of GmWRKY27 RNAi and GmWRKY27 in soybeans results in increased tolerance and hypersensitivity to drought and salt stress, respectively. In the same study, the association of GmWRKY27 with GmMYB174 was observed, which binds to neighbouring cis-elements

**Gene family Gene Studied plant Ref.** R2R3-MYB transcription factor GmMYB84 Soybean [157]

bZIP transcription factor GmFDL19 Soybean [159]

DREB transcription factor GmDREB2 Tobacco [161] AP2/ERF transcription factor GmDREB2A;2 Soybean [162] AP2/ERF transcription factor GmERF3 Tobacco [163] AP2/ERF transcription factor GmERF4 Tobacco [164] WRKY family GmWRKY54 Arabidopsis [156] WRKY family GsWRKY20 Arabidopsis [165] NAC family GmNAC20 Soybean [166] Homeodomainleucine zipper (HD-Zip) proteins Multiple HD-Zip genes Soybean [167]


**Table 3.** Major families of TF genes expressed in response to drought stress in plants.

GmGT-2A Arabidopsis

C2 H2 GmMYBJ1 Arabidopsis [158]

GmbZIP1 Arabidopsis [160]

In recent years, the advent of molecular marker technologies has opened up new opportunities for QTL analyses, fine mapping and cloning of genes for water stress tolerance. The genetic basis of drought and flooding tolerance has been studied by evaluating different component traits in drought and flood-tolerant soybean. Both drought and flooding tolerance are quantitatively inherited and controlled by several genetic loci. Consequently, a large number of QTLs related to flooding tolerance are summarized in **Table 4**.

The analysis of quantitative trait loci (QTLs) for water-logging tolerance in soybean is usually challenging. However, several studies have been done on QTLs associated to flooding tolerance, focused on injury score and tolerance index in soybean [91, 176–179, 182]. For instance, a single QTL located on Chr. 18 (Sat\_064) was identified using 208 lines of two recombinant inbred (RI) populations, for soybean growth and grain yields under water-logging conditions [176].


**Table 4.** A summary of QTL mapping studies for flood tolerance traits in soybean.

The results indicated that the Sat\_064 QTL is unique in response to flooding. The Sat\_064 QTL was further confirmed in a southern cultivar Archer using near-isogenic lines (NILs) [183]. In addition, two flooding-tolerance QTLs on Chr. 5 (Satt385) and Chr.13 (Satt269) were identified associated with water-logging tolerance through partial linkage mapping and bulk-segregation analysis using two populations [177]. Seven loci were detected associated with yield in response to flooding in a mapping population between Misuzudaizu and Moshidou Gong 503. Among them, only a large and stable QTL, *ft1* tightly linked with flowering was reproducible with high LOD score in 2 years, 2012 and 2013 (15.41 and 7.57) [178].

In another experiment, four QTLs, *Sft1, Sft2, Sft3 and Sft4* associated with seed-flooding tolerance, during geminating stage, were detected using population derived from cross between a tolerant 'Peking' (black seed coat) × susceptible cultivar 'Tamahomare' (yellow seed coat). Among these QTLs, *Sft1* located on Chr.12 had great effect on germination rate, whereas *sft2* mapped on Chr. 8 had contribution in seed coat pigmentation [91]. Two QTLs, *FTS-11* and *FTS-13* were mapped on Chr. 11 and Chr.13, respectively, using F<sup>7</sup> recombinant inbred lines (RILs) at an early reproductive stage. These QTLs were also related with flooding yield index and flooding injury score. The major QTL *FTS-13*, with phenotypic variation 18.3% was detected in multiple locations and years [179]. Recently, QTLs for root surface area development (RSAD) and root length development (RLD) on Chr. 12 (between markers Satt052 and Satt302) were identified in relation to hypoxia tolerance using F8:9 RILs derived from a cross between Iyodaizu and Tachinagaha in soybean. For the validation of these major and stable QTLs, NILs with the QTL region were developed derived from Iyodaizu [181].

#### *3.2.2. Transcriptome analysis of soybean under water stress*

Transcript abundance analysis is vital functional genomics tools to examine flooding responsive mechanisms and identify genes responsible for flooding tolerance. Recently, genome-wide changes associated with gene-expression are investigated through microarray chip analysis, RNA-seq approach and high-coverage gene expression profiling analysis for better understanding the transcriptional response in relation to flooding stress in soybean (**Table 5**). Transcripts were examined in the root tip, including the hypocotyl of soybean, using high-coverage gene expression profiling analysis; 5831 out of 29,388 were significantly altered under water stress. Genes relevant to ethylene biosynthesis, alcoholic fermentation and cell wall relaxation are promptly up-regulated in response to flooding. Defence-related genes, haemoglobin, and Kunitz trypsin protease inhibitor and acid phosphatase are responsible for flooding [184].

3498 genes were differentially expressed in response to drought and flooding stress, respectively, which contain 289 TFs demonstrating ethylene response factors (ERFs), basic helix-loop helix (bHLH), WRKY amino acid motif (WRKY), myeloblastosis (MYB) and no apical meri-

**/proteins characterized Ref**

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[186]

47

[189]

[190]

97 genes and 34 proteins [184]

Adaptation to Water Stress in Soybean: Morphology to Genetics

31 genes [187]

17 proteins [188]

146 proteins [191]

97 proteins to flooding, 48 for drought [189]

97 proteins in response to flooding and 48 proteins for drought

Three S-adenosylmethionine synthetases (SAMs) proteins

2724 genes for drought and 3498 genes for flooding, 289 Transcription

Soybean microarray chip More than 6000 genes [185]

Factors

RNA-seq based transcriptomic analysis resulted in detection of 729 and 255 genes in the flooding-tolerant line and ABA-treated soybean, respectively, which were significantly changed under stress condition. Transcript profiles also revealed that a total of 31 genes included 12 genes involved in the regulation of RNA and protein metabolism were commonly altered between the flooding-tolerant line and ABA-treated soybean under flooding stress [187]. On the basis of the above findings, it can be concluded that transcript profiles can be helpful as an

Different proteomics techniques i.e. mass spectroscopy (MS)-based (for identification of a number of environmental stress-responsive proteins), two-dimensional (2D) gel-based (for visual illustration of the proteins) and SDS gel or gel free-based (for detection of the largest number of proteins) are extensively used under water stress (**Table 5**). The available genomic information in soybean genome database helps to identify water stress-responsive mechanism. Distinct

stem (NAC) are involved in stress tolerance mechanism [186].

**Stress Tissues Platform DEG\***

Roots Gel-free proteomic

Root tip Gel-free/label-free

Roots Gel-free proteomic

profiling

Leaf tissue Illumina Genome Analyzer

(San Die go, CA) platform

RNA sequencing-based transcriptomic analysis

Gel-free/label-free proteomic technique

proteomic analysis

XL Orbitrap mass spectrometry (MS)

technique

technique

**Table 5.** Soybean transcriptome and proteome studies under flooding and drought stress.

Flooding Root and hypocotyl High coverage expression

Root tips, root with hypocotyl and cotyledons

Leaf, hypocotyl, and

Flooding Root and cotyledon Nano spray LTQ

Flooding Roots including hypocotyl

root

\*Differentially Expressed Gene.

Drought & flooding

Flooding stress

Drought & flooding

Drought & flooding

Drought & flooding

Flooding & drought

adaptive mechanism for soybean survival under water stress.

*3.2.3. Proteomics techniques for identification of water stress-responsive mechanisms*

In another study, soybean microarray chip-based transcriptomics technique was used to comprehend the molecular response under flooding. In soybean roots including hypocotyl, more than 6000 flooding-responsive genes were identified. The results revealed that genes associated with glycolysis, photosynthesis, amino acid synthesis (Ser-Gly-Cys group), transcriptional regulation of transcription, degradation of ubiquitin-mediated protein, and cell death were expressively up-regulated, whereas genes relevant to cell organization, secondary metabolism, cell wall synthesis, transport of metabolite and chromatin structure were considerably downregulated. Furthermore, up-regulation of flooding-responsive genes encoding small proteins plays key roles in acclimation to flooding [185]. It has been reported that a total of 2724 and


**Table 5.** Soybean transcriptome and proteome studies under flooding and drought stress.

The results indicated that the Sat\_064 QTL is unique in response to flooding. The Sat\_064 QTL was further confirmed in a southern cultivar Archer using near-isogenic lines (NILs) [183]. In addition, two flooding-tolerance QTLs on Chr. 5 (Satt385) and Chr.13 (Satt269) were identified associated with water-logging tolerance through partial linkage mapping and bulk-segregation analysis using two populations [177]. Seven loci were detected associated with yield in response to flooding in a mapping population between Misuzudaizu and Moshidou Gong 503. Among them, only a large and stable QTL, *ft1* tightly linked with flowering was reproducible with high

In another experiment, four QTLs, *Sft1, Sft2, Sft3 and Sft4* associated with seed-flooding tolerance, during geminating stage, were detected using population derived from cross between a tolerant 'Peking' (black seed coat) × susceptible cultivar 'Tamahomare' (yellow seed coat). Among these QTLs, *Sft1* located on Chr.12 had great effect on germination rate, whereas *sft2* mapped on Chr. 8 had contribution in seed coat pigmentation [91]. Two QTLs, *FTS-11* and *FTS-13* were

reproductive stage. These QTLs were also related with flooding yield index and flooding injury score. The major QTL *FTS-13*, with phenotypic variation 18.3% was detected in multiple locations and years [179]. Recently, QTLs for root surface area development (RSAD) and root length development (RLD) on Chr. 12 (between markers Satt052 and Satt302) were identified in relation to hypoxia tolerance using F8:9 RILs derived from a cross between Iyodaizu and Tachinagaha in soybean. For the validation of these major and stable QTLs, NILs with the QTL region were

Transcript abundance analysis is vital functional genomics tools to examine flooding responsive mechanisms and identify genes responsible for flooding tolerance. Recently, genome-wide changes associated with gene-expression are investigated through microarray chip analysis, RNA-seq approach and high-coverage gene expression profiling analysis for better understanding the transcriptional response in relation to flooding stress in soybean (**Table 5**). Transcripts were examined in the root tip, including the hypocotyl of soybean, using high-coverage gene expression profiling analysis; 5831 out of 29,388 were significantly altered under water stress. Genes relevant to ethylene biosynthesis, alcoholic fermentation and cell wall relaxation are promptly up-regulated in response to flooding. Defence-related genes, haemoglobin, and Kunitz trypsin protease inhibitor and acid phosphatase are responsible for flooding [184].

In another study, soybean microarray chip-based transcriptomics technique was used to comprehend the molecular response under flooding. In soybean roots including hypocotyl, more than 6000 flooding-responsive genes were identified. The results revealed that genes associated with glycolysis, photosynthesis, amino acid synthesis (Ser-Gly-Cys group), transcriptional regulation of transcription, degradation of ubiquitin-mediated protein, and cell death were expressively up-regulated, whereas genes relevant to cell organization, secondary metabolism, cell wall synthesis, transport of metabolite and chromatin structure were considerably downregulated. Furthermore, up-regulation of flooding-responsive genes encoding small proteins plays key roles in acclimation to flooding [185]. It has been reported that a total of 2724 and

recombinant inbred lines (RILs) at an early

LOD score in 2 years, 2012 and 2013 (15.41 and 7.57) [178].

mapped on Chr. 11 and Chr.13, respectively, using F<sup>7</sup>

*3.2.2. Transcriptome analysis of soybean under water stress*

developed derived from Iyodaizu [181].

46 Plant, Abiotic Stress and Responses to Climate Change

3498 genes were differentially expressed in response to drought and flooding stress, respectively, which contain 289 TFs demonstrating ethylene response factors (ERFs), basic helix-loop helix (bHLH), WRKY amino acid motif (WRKY), myeloblastosis (MYB) and no apical meristem (NAC) are involved in stress tolerance mechanism [186].

RNA-seq based transcriptomic analysis resulted in detection of 729 and 255 genes in the flooding-tolerant line and ABA-treated soybean, respectively, which were significantly changed under stress condition. Transcript profiles also revealed that a total of 31 genes included 12 genes involved in the regulation of RNA and protein metabolism were commonly altered between the flooding-tolerant line and ABA-treated soybean under flooding stress [187]. On the basis of the above findings, it can be concluded that transcript profiles can be helpful as an adaptive mechanism for soybean survival under water stress.

#### *3.2.3. Proteomics techniques for identification of water stress-responsive mechanisms*

Different proteomics techniques i.e. mass spectroscopy (MS)-based (for identification of a number of environmental stress-responsive proteins), two-dimensional (2D) gel-based (for visual illustration of the proteins) and SDS gel or gel free-based (for detection of the largest number of proteins) are extensively used under water stress (**Table 5**). The available genomic information in soybean genome database helps to identify water stress-responsive mechanism. Distinct changes in the soybean proteome during water stress lead to different defence mechanisms. Several studies evidently revealed that some proteins regulating sucrose accumulation, glucose degradation, cell wall relaxing, signal transduction and alcohol fermentation were altered under flooding stress [192, 193]. Flooding stress reduced the differential regulation of proteins involved in maintaining the structure of cell and protein folding [99]. Moreover, the application of exogenous calcium on flooded soybeans up-regulated the lipid metabolism, signallingrelated proteins, glycolysis-related proteins and fermentation in roots [189]. A reduction in calcium oxalate crystals was found in cotyledon under flooding [188].

After six generations, the resulting drought line was selected and further crossed with jindou14. Finally, Jindou 21 was developed after 7 years of selection in arid region of western Shanxi and depicted increased yield under water stress [196]. Xu et al. also identified 463 Chinese strains having high level of drought tolerance through breeding. These strains could be used as a potential source for enhancing drought resistance in soybean [197]. Development of RILs population for flooding tolerance is a long and tedious process. For example, in soybean, to develop F7 population by crossing S992281 X PI4081051 (high yield, flooding tolerant) via single-seed descent

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To deal with complex nature of drought and flooding, marker-assisted selection to identify QTL can be used as a promising approach. Time consuming phenotypic characterization of large population to get an effective QTL is a major challenge to improve agronomic traits associated with drought and flooding tolerance. If molecular markers are closely linked to the target QTL, it would be possible to transfer character into commercial cultivar through markerassisted breeding. Marker-assisted selection can be effectively used in soybean having high linkage disequilibrium (low recombinant frequency) [198]. For example, four QTLs associated with root morphology were detected by using 629 SSR markers, indicating that fibrous roots QTL may be related with drought tolerance and seed yield in soybean [144]. In another study, three QTLs for flooding tolerance were detected using 360 SSR markers in soybean. Among three QTLs, one major QTL exhibited large impact on flooding tolerance environments [178].

Genetic engineering in the twenty-first century is a perquisite tool in cell and molecular biology that will provide additional approaches for genetic modification by overexpression or gene silencing, protein sub-cellular localization, transposon mutagenesis and promoter characterization for permitting the development of novel and genetically diverse genotypes. These techniques have become profound strategies in soybean breeding which provide unique chances to modify the genetic makeup of soybean. Recent advancement in genetic mapping and the identification of new drought and flooding stress-responsive genes from various organisms allow researchers to modify plants using several genetic strategies. Genetic transformation in soybean was first reported in 1988 [199, 200], but the stable transformation of soybeans is still a challenging task. Several studies reported on soybean transformation by Agrobacterium-mediated transformation and particle bombardment methods [201, 202]. Both approaches have been used successfully for genetic transformation of soybean. The success is mainly dependent on the efficient delivery of transforming DNA and the recovery of transgenic lines from a transformed cell. Transgenic soy-

bean expressing GMFDL19 gene enhanced tolerance towards drought stress [159] .

Over the past 20 years, several new breeding techniques have been developed and are being implemented to facilitate breeding for the crop improvement. New breeding techniques (NBTs) give the ability to accurately modify DNA by editing DNA and genes on or off. Gene

method requires 7 years. Hence, conventional breeding approach is less useful [179].

**4.2. QTL mapping and marker-assisted selection**

**4.3. Genetic engineering**

**4.4. Other new breeding techniques**

Wang et al. identified three *S*-adenosylmethionine synthetases (SAMs) proteins using gel-free proteomic analysis under water stress in soybean. The SAMs action declined at early-stage flooding but increased in hypocotyls and roots under water deficit. The results recommended that SAMs were involved in response to water stress and it might affect ethylene biosynthesis in soybean. The action of SAMs was different in hypocotyls, root tips and roots under water stress. The down-regulation of *SAMs 1* and *SAMs 2* were observed in roots under drought and flooding. Moreover, up-regulation of ACC synthase was examined under drought, whereas the expression was down-regulated in root tips under flooding. However, ACC oxidase was increased under both stresses. These findings indicate that SAMs have key role in ethylene biosynthesis in soybean [194]. A quantitative proteomics study has been conducted for the better understanding of flooding responsive mechanisms using flooding-tolerant mutant and abscisic acid (ABA)-treated soybean. A total of 146 proteins were usually altered at the early stage of flooding. Proteins related to protein synthesis such as nascent polypeptide-related complex and chaperonin 20, and RNA regulation-associated proteins were up-regulated both at protein and mRNA expression. However, these identified proteins at early stage of flooding were not meaningfully altered. This study suggested that proteins associated with protein synthesis and RNA regulation can influence in triggering tolerance to flooding stress [195]. Therefore, proteomic approaches can be used to understand the response mechanism to drought and flooding stress at the initial stage of soybean growth.

### **4. Improvement of soybean tolerance to drought and flooding stress**

#### **4.1. Breeding objectives and progress of conventional breeding**

The objective of soybean breeding programs is to develop cultivars with enhanced yield (more pods/plant, more seeds/pod, 100-seed weight), seed composition (high protein and oil contents), shattering resistance and tolerance to abiotic and biotic stress. Many important agronomic traits (qualitative or simply inherited) are incorporated into commercial cultivar through conventional breeding. As drought and flooding are complex quantitative traits, breeders face difficulties to improve these traits through conventional breeding. Moreover, conventional breeding is tedious, labour extensive, requires a considerable time (8–9 years) and a large amount of space for evaluation. For example, in China, Jindou 21 is an excellent example of drought-tolerant cultivar developed through selective breeding. Initially, Lin Xian White (higher drought tolerance, low yield soybean cultivar) was crossed with Jindou 2 (drought tolerant and high yield). After six generations, the resulting drought line was selected and further crossed with jindou14. Finally, Jindou 21 was developed after 7 years of selection in arid region of western Shanxi and depicted increased yield under water stress [196]. Xu et al. also identified 463 Chinese strains having high level of drought tolerance through breeding. These strains could be used as a potential source for enhancing drought resistance in soybean [197]. Development of RILs population for flooding tolerance is a long and tedious process. For example, in soybean, to develop F7 population by crossing S992281 X PI4081051 (high yield, flooding tolerant) via single-seed descent method requires 7 years. Hence, conventional breeding approach is less useful [179].

#### **4.2. QTL mapping and marker-assisted selection**

To deal with complex nature of drought and flooding, marker-assisted selection to identify QTL can be used as a promising approach. Time consuming phenotypic characterization of large population to get an effective QTL is a major challenge to improve agronomic traits associated with drought and flooding tolerance. If molecular markers are closely linked to the target QTL, it would be possible to transfer character into commercial cultivar through markerassisted breeding. Marker-assisted selection can be effectively used in soybean having high linkage disequilibrium (low recombinant frequency) [198]. For example, four QTLs associated with root morphology were detected by using 629 SSR markers, indicating that fibrous roots QTL may be related with drought tolerance and seed yield in soybean [144]. In another study, three QTLs for flooding tolerance were detected using 360 SSR markers in soybean. Among three QTLs, one major QTL exhibited large impact on flooding tolerance environments [178].

#### **4.3. Genetic engineering**

changes in the soybean proteome during water stress lead to different defence mechanisms. Several studies evidently revealed that some proteins regulating sucrose accumulation, glucose degradation, cell wall relaxing, signal transduction and alcohol fermentation were altered under flooding stress [192, 193]. Flooding stress reduced the differential regulation of proteins involved in maintaining the structure of cell and protein folding [99]. Moreover, the application of exogenous calcium on flooded soybeans up-regulated the lipid metabolism, signallingrelated proteins, glycolysis-related proteins and fermentation in roots [189]. A reduction in

Wang et al. identified three *S*-adenosylmethionine synthetases (SAMs) proteins using gel-free proteomic analysis under water stress in soybean. The SAMs action declined at early-stage flooding but increased in hypocotyls and roots under water deficit. The results recommended that SAMs were involved in response to water stress and it might affect ethylene biosynthesis in soybean. The action of SAMs was different in hypocotyls, root tips and roots under water stress. The down-regulation of *SAMs 1* and *SAMs 2* were observed in roots under drought and flooding. Moreover, up-regulation of ACC synthase was examined under drought, whereas the expression was down-regulated in root tips under flooding. However, ACC oxidase was increased under both stresses. These findings indicate that SAMs have key role in ethylene biosynthesis in soybean [194]. A quantitative proteomics study has been conducted for the better understanding of flooding responsive mechanisms using flooding-tolerant mutant and abscisic acid (ABA)-treated soybean. A total of 146 proteins were usually altered at the early stage of flooding. Proteins related to protein synthesis such as nascent polypeptide-related complex and chaperonin 20, and RNA regulation-associated proteins were up-regulated both at protein and mRNA expression. However, these identified proteins at early stage of flooding were not meaningfully altered. This study suggested that proteins associated with protein synthesis and RNA regulation can influence in triggering tolerance to flooding stress [195]. Therefore, proteomic approaches can be used to understand the response mechanism to drought and flooding stress

**4. Improvement of soybean tolerance to drought and flooding stress**

The objective of soybean breeding programs is to develop cultivars with enhanced yield (more pods/plant, more seeds/pod, 100-seed weight), seed composition (high protein and oil contents), shattering resistance and tolerance to abiotic and biotic stress. Many important agronomic traits (qualitative or simply inherited) are incorporated into commercial cultivar through conventional breeding. As drought and flooding are complex quantitative traits, breeders face difficulties to improve these traits through conventional breeding. Moreover, conventional breeding is tedious, labour extensive, requires a considerable time (8–9 years) and a large amount of space for evaluation. For example, in China, Jindou 21 is an excellent example of drought-tolerant cultivar developed through selective breeding. Initially, Lin Xian White (higher drought tolerance, low yield soybean cultivar) was crossed with Jindou 2 (drought tolerant and high yield).

**4.1. Breeding objectives and progress of conventional breeding**

calcium oxalate crystals was found in cotyledon under flooding [188].

at the initial stage of soybean growth.

48 Plant, Abiotic Stress and Responses to Climate Change

Genetic engineering in the twenty-first century is a perquisite tool in cell and molecular biology that will provide additional approaches for genetic modification by overexpression or gene silencing, protein sub-cellular localization, transposon mutagenesis and promoter characterization for permitting the development of novel and genetically diverse genotypes. These techniques have become profound strategies in soybean breeding which provide unique chances to modify the genetic makeup of soybean. Recent advancement in genetic mapping and the identification of new drought and flooding stress-responsive genes from various organisms allow researchers to modify plants using several genetic strategies. Genetic transformation in soybean was first reported in 1988 [199, 200], but the stable transformation of soybeans is still a challenging task. Several studies reported on soybean transformation by Agrobacterium-mediated transformation and particle bombardment methods [201, 202]. Both approaches have been used successfully for genetic transformation of soybean. The success is mainly dependent on the efficient delivery of transforming DNA and the recovery of transgenic lines from a transformed cell. Transgenic soybean expressing GMFDL19 gene enhanced tolerance towards drought stress [159] .

#### **4.4. Other new breeding techniques**

Over the past 20 years, several new breeding techniques have been developed and are being implemented to facilitate breeding for the crop improvement. New breeding techniques (NBTs) give the ability to accurately modify DNA by editing DNA and genes on or off. Gene or genome editing including CRISPR/Cas9 is a broad category that offers an inexpensive, quick and easy technique to manipulate DNA and lessen the time and effort as compared to traditional breeding. Now-a-days, researchers are working on CRISPR/Cas9-edited versions to improve the different crops such as soybeans, rice, corn, canola and wheat with new traits like drought and flooding resistance and higher yields. Recently, various new plant breeding techniques such as zinc finger nuclease (ZFN) technology, acetate-mediated approach, oligonucleotide-directed mutagenesis (ODM), RNA-dependent DNA methylation (RdDM), cisgenesis, intragenesis, grafting (on GM rootstock) and reverse breeding allow the faster and more efficient improvement of crop varieties.

prompts the production of ethylene which prevents the inhibitory effects of high IAA on root growth [214]. Elevation in ethylene production by waterlogged plants results in wilting, necrosis, chlorosis and reduced biomass yield. The application of ACC deaminase-producing plant growth-promoting rhizobacteria (PGPR) can protect plants from these damages [215, 216]. PGPR produce ACC deaminase, which converts ACC into α-ketobutyrate and ammonia, thus reducing the levels of ethylene under water stress conditions. A combination of PGPRs, along with arbuscular mycorrhizal (AM) fungi, including ACC deaminase-producing bacteria, *Pseudomonas*, *Azospirillum*, *Rhizobium* and *Bradyrhizobium*, could be a novel step in the allevia-

Adaptation to Water Stress in Soybean: Morphology to Genetics

http://dx.doi.org/10.5772/intechopen.72229

51

Water stress has become major abiotic limitation factor on soybean production under warming climate. To combat drought and flooding stress, there is need to explore the resilient genetic resources and their utilization in breeding program. With the advancement in transcriptomics, proteomics, metabolomics, structural genomics and epigenetics, the production of soybean can be enhanced under water stress by integrating all disciplines. Recent advances in breeding system and agronomic practices will offer an opportunity for significant and predictable

This work is supported by the National Key R & D Program for Crop Breeding (2016YF D0100201), the Natural Science Foundation of China (31571691, 31771821), the MOE Program for Changjiang Scholars and Innovative Research Team in University (IRT\_17R55), and the

Key Laboratory of Biology and Genetics and Breeding for Soybean, National Center for Soybean Improvement, Ministry of Agriculture, State Key Laboratory of Crop Genetics and

[1] Wilcox JR. World distribution and trade of soybean. In: Boerma HG, Specht JE, editors. Soybeans: Improvement, Production, and Uses. Vol. 16. Agronomy Monographs. 3rd ed.

Germplasm Enhancement, Nanjing Agricultural University, Nanjing, China

tion of flooding-impacted plants.

incremental improvements in soybean under water stress.

Tuanjie Zhao\*, Muqadas Aleem and Ripa Akter Sharmin

Madison, WI, USA: ASA-CSSA-SSSA; 2004. pp. 1-14

\*Address all correspondence to: tjzhao@njau.edu.cn

**5. Conclusions**

**Acknowledgements**

Jiangsu JCIC-MCP program.

**Author details**

**References**

#### **4.5. Agronomic practices to mitigate the effects of water stress**

Agronomic practices can be mitigated the adverse effects of drought and flooding stresses by adopting various strategies. Seed priming is an effective and pragmatic technique to mitigate drought in which seeds are moderately hydrated. In this technique, germination rate, germination percentage and germination uniformity of primed seed increased [11, 203]. This approach has been useful to counteract the effects of drought stress in a range of crop species. Foliar application of plant growth regulators is another technique for improving growth against drought stress. Exogenously applied abscisic acid, uniconazole and brassinolide increased yields both under well-watered and drought conditions in soybean. Plant growth regulator treatments meaningfully increased water potential and chlorophyll contents under water stress conditions [204]. Traditional irrigation system causes >50% loss of irrigated water because of uncovered and unlined ditches. Therefore, a well-managed pipe system is required to avoid losses from traditional irrigation system as it can enhance the conveyance efficiency >90% [205]. Mulching involving covering of soil by using straw or plastic sheets, is another best strategy to retain moisture in soil. For instance, in China, soybean yield increased up to 23.4 and 50.6% by using mulching along with hole sowing and row sowing, respectively [206].

Several management practices have been tried to overcome completely or partially flooding injuries. Flooding induces nitrogen deficiencies resulting in a significant decrease in the uptake of nitrogen. As a result, yellowing of leaves occurred following 2–3 days of flooding. It has been reported that the application of nitrogen fertilizer i.e. polymer-coated urea (PCU) is effective to reduce nitrogen loss and recover flood damage in corn. It also helps to overcome oxygen deficiency in response to flooding stress preferentially [207]. Hypoxia also reduces the capacity of plant to absorb potassium (K). K plays a vital role in alleviating both biotic and abiotic stresses [208]. Indeed, K<sup>+</sup> ions are involved in detoxification of ammonium and ammonia [209], promoting photosynthesis which helps plant recovery and nutrient uptake. Foliar and soil applications oxygen-containing fertilizers lessen the drastic effects of flooding stress [210]. For example, under flooding, oxygen-containing fertilizers considerably retained chlorophyll content and biomass in Italian basil [211].

Under flooding stress, 1-aminocyclopropane-1-carboxylate (ACC) synthase enzyme along with several stress proteins were synthesized [212].The stressed plant consequently produces more ACC in their roots. In roots, ACC cannot be converted into ethylene due to insufficient oxygen. This ACC transferred from roots to shoots converting ACC to ethylene (sufficient oxygen environment) in shoots [213]. In soybean, phytohormone indole acetic acid (IAA) prompts the production of ethylene which prevents the inhibitory effects of high IAA on root growth [214]. Elevation in ethylene production by waterlogged plants results in wilting, necrosis, chlorosis and reduced biomass yield. The application of ACC deaminase-producing plant growth-promoting rhizobacteria (PGPR) can protect plants from these damages [215, 216]. PGPR produce ACC deaminase, which converts ACC into α-ketobutyrate and ammonia, thus reducing the levels of ethylene under water stress conditions. A combination of PGPRs, along with arbuscular mycorrhizal (AM) fungi, including ACC deaminase-producing bacteria, *Pseudomonas*, *Azospirillum*, *Rhizobium* and *Bradyrhizobium*, could be a novel step in the alleviation of flooding-impacted plants.
