31Rice: Genomics-Assisted Breeding for Drought TolerancePrashant Vikram, Arvind Kumar, Alok Singh, and Nagendra K. Singh

Rice is a major source of global food calories. Increasing population pressure,unpredictable rainfall patterns, shrinking fresh water resources, and increasedfrequency of severe drought spells in recent years are the reasons behind puttingconcerted efforts toward breeding drought-tolerant rice cultivarsmuchneeded by therice farmers. Attempts to breed rice for stress environments have made limitedprogress so far, but success with recent research on identification of major QTL(quantitative trait loci) for grain yield under drought shows that genomics-assistedbreeding couldbea viable alternative to enhancegrainyieldunderdrought.MajorQTLwith consistent effects on grain yield under drought and different drought-relatedtraits have beenmapped on rice chromosome 1, 2, 3, 9, and 12 and search is on for thegenes underlying these QTL. Direct selection for yield under drought has emerged asan important criterion for both conventional and molecular breeding approaches.Transgenic rice with overexpression of transcription factors such as DREB1 andSNAC1 has shown considerable promise, but its use in breeding is still impeded.

31.1Introduction

Rice is the most important food crop of the world, cultivated in an area of about 150million ha. Despite huge annual production of over 550million ton, only about 4% ofthe total production is traded in international markets. In Asia, rice supplies 35–60%of the total food calories [1]. In countries where rice is the major food source,including China, India, and Indonesia, the average annual rate of population growth(1.7%) has been higher than 1.2% average growth in rice production [2]. According toFAO estimates, the world population would be around 9.8 billion by 2050 and 75%more food would be required to feed the additional population [3]. Global warmingand unpredictable rainfall patterns in recent past have led to severe drought spellscausing huge yield losses and severe shortage in food production in several partsof the world.

Improving Crop Resistance to Abiotic Stress, First Edition.Edited by Narendra Tuteja, Sarvajeet Singh Gill, Antonio F. Tiburcio, and Renu Tuteja� 2012 Wiley-VCH Verlag GmbH & Co. KGaA. Published 2012 by Wiley-VCH Verlag GmbH & Co. KGaA.

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Rice is a semiaquatic plant that is grown under four different cropping environ-ments: irrigated, rain-fed lowland, rain-fed upland, and deep water [4]. Irrigatedrice is by far themost common ecosystem constituting 55% of the acreage and 75%of the production globally [1]. The rain-fed lowland rice constitutes the secondmostimportant ecosystem sharing 25%of the global rice area. These arefields that do notreceive irrigation water, but there are bunds around the fields that allow thewater toaccumulate on the field surface when there is rain [1]. Deep-water rice is planted inthe areas that are naturally flooded during the rainy season. This rice representsabout 8% of the total rice-growing area and here rice seeds are broadcasted a fewweeks before the beginning of themonsoon season [1]. Rain-fed upland, also calleddry land, rice is the type grown in areas where good soil drainage combined with anuneven land surface makes the accumulation of water impossible. Upland ricerepresents around 12% of world acreage and is the rice ecosystem with the lowestyields of all [1].

Rice production losses due to drought are common inmore than 23million ha ofrain-fed area in South Asia, Southeast Asia, and Sub-Saharan Africa [5, 6]. In severedrought years, total rice production losses have reached as high as 40%, valued atUS$650million in the eastern Indian states of Jharkhand,Orissa, andChhattisgarhalone [7]. In India, the 2002 drought affected 55% of the country�s area and 300million people when rice production declined by 20% from the interannualbaseline [8]. Recent drought in 2009 has resulted in 16% reduction in riceproduction leading to high price rise and food security concerns. In 2004, a severedrought affected more than 2 million ha of the cropped area in Southeast Asiaaffecting the livelihood security of over 8 million people [8]. Drought also affectsproduction in millions of hectares dependent on surface irrigation, where riverflows and water impounded in ponds and reservoirs may be insufficient to irrigatethe rice crop [9]. Water deficit is predicted to be a major challenge for sustainablerice production in future due to progressive climate change processes [100].Despite drought being a major constraint to rice production, little success hasbeen made in developing drought-tolerant rice cultivars. Most of the improvedcultivars grown in drought-prone areas are the varieties originally bred for irrigatedconditions and are highly susceptible to drought. Predicted increase in incidence ofdrought due to climate change presses the need to develop drought-tolerant high-yielding cultivars [10–12].

Drought may simply be defined as reduction in yield due to shortage of water [13].Drought in the rice crop is classified on the basis of growth stage of the crop facingdrought. Theremay be four kinds of drought: (i) seedling stage drought, (ii) vegetativestage drought, (iii) intermittent drought, and (iv) reproductive stage or terminaldrought. Reproductive stage drought is the most devastating in terms of yieldreduction [14]. Drought tolerance has long been regarded as a complex trait relatedto various physiological and biochemical parameters. These may include root traits,osmotic adjustment (OA), and maintenance of plant water status. QTL for thesecomponent traits and yield under drought have been identified and are beingemployed in molecular breeding of rice.

716j 31 Rice: Genomics-Assisted Breeding for Drought Tolerance

31.2Morphophysiological Basis and Breeding for Drought Tolerance in Rice

Rice plant employs several mechanisms to deal with the drought stress and thesemechanisms varywidely fromone cultivar to other. Plantsmay adopt shorter life cycle toescape or avoid drought or they may have phenological adaptations, for example, thickcuticles for reduced evapotranspiration and long and thick roots to enable the plant tofetch water from deeper soil layers. Physiological traits such as osmotic adjustment tomaintain cell turgor pressure duringdehydration andability to recover fromdesiccationare also important components of drought tolerance [15, 16]. Regarding traits forbreeding drought tolerance in rice, there are two important considerations, the stressresponsiveness of the trait and maintenance of plant water status (Figure 31.1, [17]).

Rice is a highly drought-susceptible plant. One of the reasons for this is its very thinlayer of epicuticular wax that is about 20% of that in sorghum, a relatively drought-tolerant crop [15]. The resistance of rice cuticle to water loss is, therefore, low and itloses water even when its stomata are closed [18, 19]. Upland rice cultivars that arerelativelymore drought tolerant usually have a thicker epicuticular wax layer than theirrigated rice cultivars, indicating that the wax layer plays an important role indrought resistance. Osmotic adjustment is another well-known phenomenon thatenables plants to survive water stress, but application of this trait in rice breeding isstill under debate. Some scientists believe that it can be an important part of thesolution leading to development of drought-tolerant rice [15, 20], whereas others areskeptical about the usefulness of this approach [18].

In upland varieties, a deeper root system enables rice plants to extract more waterfrom the lower soil layers under drought conditions [21]. In most cases, the numberof rootsmay notmatter, but thickness and length of the roots help large xylem vesselsto extract moisture even under severe stress [15, 18]. Root-to-shoot weight ratiobecomes quite important in this case.Higher the root-to-shoot weight ratio, themorea rice cultivar is likely to be tolerant to drought. However, partitioning of carbonbetween source (shoot) and sink is important here because if too much carbon isutilized for the root growth, then yield is likely to be adversely affected [22].

Flowering timeStay-green and root traits

Nonstressresponsive

Stressresponsive

Plant waterrelations

OsmoprotectantsAntioxidant agentsHeat shock proteinsMolecular chaperonesOsmotic adjustmentMembrane stability

Maintenance of leaf water potentialMaintenance of relative water content

Figure 31.1 Different categories of drought tolerance traits in rice.

31.2 Morphophysiological Basis and Breeding for Drought Tolerance in Rice j717

Lack of effective selection criteria for component traits of drought tolerance andlow heritability of grain yield under stress are cited as major reasons for the slowprogress in breeding for drought tolerance and the use of secondary traits for yieldimprovement [23–31]. Gains in yield by selecting for secondary traits have not yetbeen clearly demonstrated in rice. Significant scientific progress over the last 6 yearsin (i) stress genomics, (ii) breeding and phenotyping methodology [12, 32, 33], and(iii) better understanding of the drought tolerance mechanisms [18] has made itpromising to develop drought-tolerant varieties with high yield potential. Recentstudies at International Rice Research Institute (IRRI) have demonstrated the effec-tiveness of direct selection for grain yield under drought stress [12, 13, 34–36].Direct selection for grain yield under drought has led to release of two breedinglines developed at IRRI, namely, IR74371-70-1-1 and IR74371-54-1-1, for cultivation inIndia and Philippines, respectively, in 2009.

Breeding line IR74371-70-1-1 was developed at IRRI from IR55419-04�2/WayRarem cross, IR55419-04 being the drought-tolerant donor, and distributed toNational Agricultural Research and Education Systems (NARES) partners in2003. A selection from this line, IR 74371-70-1-1-CRR-1, was first tested at severallocations in IRRI-India Upland Rice Shuttle Breeding Network (URSBN). It wasnominated for testing under the All India Coordinated Rice Improvement Program(AICRIP) by Central RainfedUplandRice Research Station (CRURRS) of ICAR from2005 to 2007. In the AICRIP trials, it showed yield advantage of 29.2 and 19.1% overthe national and regional check varieties under drought-affected situations. It has anaverage yield advantage of 0.5 ton ha�1 under moderate drought and 1.0 ton ha�1

under severe drought over IR64. It was released by the name �Sahbhagi Dhan� forcultivation in drought-prone Jharkhand and Orissa states of India.

31.3Mapping of QTL for Drought Tolerance in Rice

Quantitative trait loci (QTL) have been identified for almost all drought-related traitsin rice. Around 20 different mapping populations have been screened both fordrought-related secondary traits and for yield under drought (Table 31.1). Slowprogress in breeding for drought-tolerant rice varieties has been attributed to failureto identify QTL with large and consistent effects on yield that could be used formarker-assisted selection [16, 37–42]. Most of the mapping populations studied forthe identification of secondary traits associated with drought tolerance have beenderived from parents that do not differ very widely for drought tolerance. Manytraditional varieties and land races of rice adapted to drought-prone areas have highlevel of drought tolerance, but they have rarely been used as parents in the QTLmapping studies. Many of the mapping populations used for QTL mapping arederived from indica/japonica crosses because they show higher markerpolymorphism [43].

Recent research at IRRI in partnership with NARES using well-characterizeddrought-tolerant donors as one of the parents in the mapping/breeding populations

718j 31 Rice: Genomics-Assisted Breeding for Drought Tolerance

Table 31.1 Different traits andmappingpopulationsused for the identification of drought toleranceQTL in rice.

Trait Population References

Osmotic adjustment, dehydrationtolerance

CO39/Moroberekan [44]

Root morphology Azucena/Bala [22]Leaf rolling, stomatal conductance Azucena/Bala [22]Root morphology, root distribution IR64/Azucena [41]Tiller number, total/penetrated rootsratio

Azucena/Bala [45]

CMS under drought CT9993/IR62266 [40]Root characteristics IR58821/IR52561 [46]Root thickness, root penetrationindex

IR64/Azucena [42]

Leaf rolling, leaf drying, RWC,growth rate

IR64/Azucena [47]

Drought-related morphological andphysiological traits

IR64/Azucena [38]

Root traits, OA CT9993/IR62266 [16]Root growth, dehydration avoidance Azucena/Bala [48]Root traits, shoot biomass CT9993/IR62266, IR58821/IR52561 [39]Yield and root traits under drought IR64/Azucena [49]Stay green character, chlorophyllcontent

Hwacheong-wr mutants [50]

Yield, biomass, OA, root traits CT9993/IR62266 [37]Root traits IR1552/Azucena [51]Yield components under drought Bala/Azucena [52]Yield components under drought Introgression lines [53]Dehydration avoidance Indica� Japonica [54]Dehydration avoidance O. rufipogon introgression lines [55]Dehydration avoidance IR58821/IR52561 [56]Root length (constitutive) Kalinga III/Azucena [57]Yield under lowland drought stress CT9993/IR62266 [58]Yield under drought at reproductivestage

Vandana/Way Rarem [59]

Morphophysiological traits, yieldunder drought

Taking background [60]

Growth and development underPEG stress

Akihikari/IRAT109 [61]

Leaf epicuticular wax and other traitresponses under drought

CT9993-5-10-1-M/IR62266-42-6-2 [62]

Yield under drought at reproductivestage

N22/Swarna, N22/IR64, N22/MTU1010 [63, 64]

Yield under drought at reproductivestage

Apo/Swarna [65]

Drought resistance traits IR20/Nootripathu [66]

31.3 Mapping of QTL for Drought Tolerance in Rice j719

has identified QTL with major and consistent effect on rice yield under drought[58, 59, 65]. Bernier et al. reported a QTL on chromosome 12 (qDTY12.1) in theVandna/Way Rarem population that explained 51% of the genetic variance for yieldunder drought [59]. Till now this QTL has shown the largest effect for grain yieldunder drought in several genetic backgrounds. The qDTY12.1 also showed largeand consistent effect in target environments in a wide range of moderate to severedrought situations [67, 68]. A major QTL for grain yield under lowland drought,explaining 32% of the phenotypic variance, was reported on rice chromosome 1 inCT9993/IR62266 population [58]. Subsequent studies have identified major QTLwith consistent effect on grain yield under lowland drought on chromosome 2(qDTY2.1) and 3 (qDTY3.1) in Apo/2�Swarna mapping population. The DTY2.1 andDTY3.1 QTL explain 13–16 and 31% of the phenotypic variance of the trait, respec-tively, rendering them useful for marker-assisted breeding for yield under lowlanddrought stress [65]. Recently, a common QTL for yield under drought (qDTY1.1) hasbeen reported in three different mapping populations involving Indian drought-tolerant variety N22 [63, 64].

In case of new rice for Africa (NERICA), drought tolerance QTL have beenintroduced from Oryza glaberrima into O. sativa, producing better-adapted alienintrogression lines for drought-prone areas of African continent [48]. QTL for yieldhave also been identified inO. rufipogon and otherwild rice species thatmay provide asource of new genes for drought tolerance [45, 48, 69, 70]. This approach also opensup opportunities for the application of genomics for the identification of droughttolerance genes. Comparative genome analysis shows that some of the droughttolerance QTL identified in rice have their homologues in other crop species, forexample, barley andmaize, indicating that genes conferring drought tolerance in onegrass speciesmay have a similar effect on another species of this family. These genesseem to be conserved inmany different grass species during the course of evolution;therefore, knowledge gained from the research carried out in rice will be useful inbreeding other cereal crops and vice versa [16].

31.4Meta-Analysis of Drought Tolerance QTL in Rice

A large number of minor QTL for different drought-related traits have been mappedon almost all the 12 rice chromosomes. Therefore, the use of bioinformatics tools hasbecome imperative for the identification of consensus QTL and candidate genes.Meta-analysis combines the results of several QTL mapping studies and providesnarrow confidence intervals for meta-QTL. This simplifies the identification andpositional cloning of the candidate genes.Meta-analysis is usually applied tomultiplemapping populations, but it can be applied to a single population as well [71].Combining QTL data from studies employing different mapping populations wouldbe extremely helpful in identifying candidate genes by positioning consistent QTLwith more precision. Meta-analysis of QTL enables us to work out �hot spot� regionsin the genome. Within those regions, one can look for the gene(s) underlying QTL

720j 31 Rice: Genomics-Assisted Breeding for Drought Tolerance

more precisely. This approach has already been applied for the analysis of root traitQTL in rice [72]. Interestingly, a QTL mapped on the long arm of chromosome 1 forgrain yield under drought in different populations emerged as one of the hot spots forthe root trait QTL in the meta-analysis [72].

31.5Marker-Assisted Selection and Pyramiding of Drought Tolerance QTLin Elite Rice Cultivars

A large number of QTL have been identified in rice for drought tolerance and yieldunder drought, but their introgression in the popular varieties of rice has just begun.Themajor drawback in this approach is the linkage drag – transfer of undesired traitsalong with the trait of interest due to their tight genetic linkage. One of the mostsuccessful examples of marker-assisted backcross breeding in rice for abiotic stresstolerance is introgression ofSub1 gene for submergence tolerance into popularmegavariety of rice �Swarna� to create Swarna-sub1, where three kinds of markers wereused: (i) a gene-based functional marker for the selection of favorable Sub1 allele,(ii) two markers flanking the QTL to eliminate the linkage drag, and (iii) randombackground markers for fast recovery of the genetic background of the recipientvariety during backcrossing [73]. Drought-tolerant donors in most populationsscreened for the QTL analysis are traditional varieties with low-yield potential, poorresponse to high-input management, early duration, taller plants, and sometimescarrying undesirable characteristics such as high grain shattering. One or more ofsuch undesirable traits may be located near the drought QTL regions, hence apotential linkage drag in breeding for drought tolerance.

Despite the large number of drought tolerance QTL identified, limited attemptshave been made for the introgression of these QTL into high-yield breeding lines[43, 69]. The limited success in the past may be due to involvement of minor QTLexplaining very small proportion of the total phenotypic variation (5.6–17.7%) andlack of adequate fine mapping to develop tightly linked markers for breedingapplications. As a result, the desirable genes could be lost due to recombinationbetween gene for the trait and the marker during backcrossing [74]. Recent progressin identification and fine-mapping of major QTL for yield under drought has pavedthe way for introgression of suchQTL inmega rice varieties throughmarker-assistedbackcrossing in the near future.

Marker-assisted selection (MAS) could be applied with some modification ofstrategies such as single large-scale marker-assisted selection (SLS-MAS) and mark-er-assisted recurrent selection (MARS) [75, 76]. The main features of SLS-MAS arethat (i)MAS could be performed at F2 or preferably F3 populations derived from elitelines, (ii) flanking markers are less than 5 cM away from the QTL, and (iii) QTLchosen should explain large proportion of the phenotypic variation and be stableacross environments. This involves a four-step procedure: (i) identification of elitelines outstanding for the trait of interest, (ii) identification of the most favorablegenomic regions for each parental line, (iii) intercrossing of elite lines to develop

31.5 Marker-Assisted Selection and Pyramiding of Drought Tolerance QTL in Elite Rice Cultivars j721

segregating populations, and (iv) selection of plants homozygous for the favorablealleles at target loci.

Pyramiding of QTL is another approach for breeding drought-tolerant rice. A largenumber of QTL introgression lines (ILs) could be created in elite backgrounds usingbackcross (BC) breeding, each of which carries different genomic segments forimproved drought tolerance from known donors. The ILs are then intercrossed topyramid all QTL into one variety (Figure 31.2). A drawback of this approach is thelinkage drag from donor parents used for the introgression of different QTL.Therefore, this needs to be approached with utmost care, particularly when targetingintrogression of several QTL into one line [77].

31.6Comparative Genomics for Drought Tolerance

Comparative mapping of the genomic regions across species is an interestingalternative for the identification and positional cloning of the candidate genesunderlying drought tolerance QTL. QTL for leaf water potential, relative watercontent, and other drought-related traits have been identified on barley chromosome7 H [78]. Leaf water potential and RWC QTL are also identified at orthologousposition on rice chromosome 8 in the C039/Moroberekkanmapping population [44].A major gene called Or controlling osmoregulation has been identified at the sameorthologous position in wheat chromosome 7A [79]. The synteny and colinearity ofgenes among cereals is muchmore complex with many exceptions, and it is difficult

Figure 31.2 Schematic plan for simultaneous but stepwise method for transfer of droughttolerance QTL/genes from multiple donors in rice (A. K. Singh, Genetics, IARI, New Delhi).

722j 31 Rice: Genomics-Assisted Breeding for Drought Tolerance

to find comparable QTLmap locations in cereals due to polyploidy and transpositionof genes [80]. However, such analysis is possible bymicrosynteny analysis for similarQTL regions in different cereals as shown in the above example of the Or gene.

31.7Transcriptomics and Proteomics for the Identification of Drought ToleranceGenes in Rice

Since hot spots for drought tolerance QTL in the rice genome are known, it is nowrelatively simple to identify differentially expressed candidate genes in these regionsfor understanding drought tolerance in rice. In silico analyses have been carried outfor theQTL regionsflanked by themolecularmarkers and candidate genes identifiedthrough functional homology. A study has identified 48 candidate genes on ricechromosome 1 betweenmarkers RM212 andRM319, of which 16were suggested fortheir potential role in drought tolerance [81]. Similar in silico analyses have been doneand candidate genes identified on chromosome 1, 2, 4, 8, and 9 [82]. Severaltranscription factor genes, for example, CBF/DREB1, DREB2, RD29B, RD22, ICE1,CDPK, ABF3, CBF3, and SNAC1 have been studied for their differential expressionand regulatory role under drought stress [83–86]. Some of these genes have beentransferred to rice through transgenic approach to validate their role in drought stresstolerance (Table 31.2).

Table 31.2 List of transcription factors genetically transformed in rice for drought tolerance.

Gene Trait References

HVA1 (barley group 3 LEA protein) Drought and salt [87]P5CS, encoding pyrroline-5-carboxylate synthetase Drought [88]OsCDPK7 (rice calcium-dependent protein kinase) Cold, drought, salt [85]TPS (trehalose-6-phosphate synthase), TP (trehalose-6-phosphatase)

Drought [89–91]

Dadc (D. stramonium arginine decarboxylase) Drought [92]RWC3 Drought [93]ABF3 (Arabidopsis ABRE-binding factor 3) Drought [84]DREB1A (Arabidopsis DRE-binding protein 1) Drought and salt [84]MnSOD (pea Mn superoxide dismutase) Drought [94]SNAC1 (rice stress-responsive NAC1) Drought and salt [83]OsDREB1 (rice DRE binding protein 1) Drought, salt, cold [95]HvCBF4 (barley C-repeat binding factor) Drought, salt, cold [96]OsCIPK12 (rice calcineurin B-like protein-interactingprotein kinase 12)

Drought [97]

OCPI1 Drought [98]ZFP252 (rice TFIIIA-type zinc finger protein) Drought, salt [99]OsDHODH1 Drought, salt [100]ONAC045 (NAC gene) Drought, salt [101]

31.7 Transcriptomics and Proteomics for the Identification of Drought Tolerance Genes in Rice j723

Most of the genes presumed to be involved in the drought tolerance are involved in(i) signal transduction, (ii) osmotic adjustment, and (iii) transcriptional regulation ofthe stress response pathway, for example, DREB1 and SNAC1. Transgenic rice withoverexpression of SNAC1 gene showed 22–34% higher seed setting than controlplants [83]. However, successful commercialization of these transgenic lines is stillquestionable due to complex gene interactions. Despite considerable progress in thedevelopment of transgenic rice lines, their impact on enhancing drought toleranceunder field conditions is still awaited. These lines need to be tested in field droughtenvironments and for their biosafety and other regulatory issues prior to theirdeployment in popular rice varieties through marker-assisted backcross breeding.Screening of transgenic plants for drought tolerance has been usually done undercontrolled glasshouse, but selection for drought-tolerant rice varieties is advocated inthe target drought-prone environments [102, 103].

Proteomics approach has also been followed by someworkers, andmore than 2000proteins were analyzed by 2D electrophoresis [104]. Drought-induced changes wereobserved in actin depolymerizing factor (ADF), which is a chloroplastic glutathione-dependent dehydroascorbate reductase. ADF concentration was higher in drought-tolerant cultivars before stress and it increased further in leaf blades, leaf sheaths, androots after exposure to drought, suggesting that ADF could be one of the targetproteins for drought tolerance [105]. Differentially expressed proteins could beworked out through protein profiling of the mapping populations.

31.8Conclusions

Rice is a semiaquatic species highly susceptible to drought. Global warming,unpredictable rainfall patterns, and climate change would cause more severe stresssituations in the rain-fed agriecosystems in future. Efforts for developing drought-tolerant rice varieties through conventional breeding by direct selection for grainyield under drought have yielded some success, and molecular breeding approachesare now beginning to be employed for introgression of major QTL for grain yieldunder drought. Genes underlying these QTL are being deciphered using genomicsapproaches. Transgenic rice plants have also been developed with transcriptionfactors such as DREB1 and SNAC1, but these need to be evaluated under fielddrought environment to validate their actual potential for increasing rice production.However, drought tolerance is a complex trait and discovery of useful alleles of thegenes involved in the drought response pathway requires extensive use of genomicsapproaches and high-precision phenotyping employing modern phenomic facilitiesin addition to repeated field phenotyping in the target environment.

Acknowledgment

The first author gratefully acknowledges the financial support of IRRI studentshipduring this study.

724j 31 Rice: Genomics-Assisted Breeding for Drought Tolerance

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