| Sustainable agriculture and food security are two key issues greatly threatened by the climatic changes.Legumes being rich in proteins have thereby a unique role in alleviating the hunger and poverty from the world and thus leading to a sustainable resilient agriculture.Soybean[Glycine max(L.)Merr.]is an important legume crop worldwide for providing food for human and feed for livestock.However soybean is facing drought as one of the major yield constraints.Soybean is sensitive to drought at almost all of its growth stages.The damage to crop depends upon stress duration and its severity,sometimes resulting in the replanting of the crop.This situation has forced agricultural research to focus on efficient utilization of limited water resources by developing and applying agricultural technologies relating to breeding cultivars tolerant to drought stress.Drought tolerance(DT)is a complex quantitative trait controlled by the polygenes/QTLs.Thus the identification of QTL is considered to be a great achievement in breeding.Generally,linkage mapping(LM)and association mapping(AM)are two commonly used procedures employed for dissecting the genetic architecture of complex traits.The classical LM is based on bi-parental crossing has been quite effective in identifying large number of loci for DT.However resolving small effect QTLs using the bi-parental mapping population is a significant challenge for the breeders.Therefore developing the multiple parental crossing designs bringing alleles across different locations increase the diversity and resolution of QTLs are suggested.The nested association mapping(NAM)takes advantage of multi-parental lines with multiple alleles per locus and large population size and has emerged as a promising multi-parental mapping design for complex trait genetic dissections.To evaluate the DT,different indicators,such as water use efficiency,leaf hydraulic conductance,leaf water status traits etc,have been suggested.However,each of these indicators may involve with only individual biological process.In plant breeding,comprehensive DT indicator(s)are preferred for thorough evaluation and thus representing the overall perspective of DT.Therefore,the growth traits,such as plant,shoot,root lengths and dry weights are considered as suitable DT indicators because all the individual DT biological processes will be finally reflected in plant growth and its end products.Until now which indicator(s)can be used as a comprehensive measure of DT,was not known.For effective utilization of germplasm in plant breeding,the basic step is to explore the population’s genetic constitution;including the genes/QTLs with their corresponding alleles.Association mapping(AM)applied directly to breeding populations has been suggested to mitigate the lack of relevance of biparental populations in QTL identification.However this practice has the demerit of biased effect estimates and therefore leads to poor prediction of line performance.Furthermore,for thorough and accurate QTL detection in the germplasm,the AM strategy has to involve multiple alleles on each locus,to control the overflowing and missing heritability,and to correct the population bias resulted from admixtures and inbreeding.An innovative restricted two-stage multi-locus GWAS procedure(RTM-GWAS)was suggested to resolve these issues.DT being a complex trait needs to be assessed by different stress inducing techniques.Generally DT experiments are performed either growing plants in soil/sand and using the method of water withholding or by growing the plants in a solution of high osmotic potential using some chemical(e.g,Polyethylene glycol,mannitol etc).For working out the best test system which could be used for selecting the genotypes for DT,we designed the experiments by growing the NAM population in Sand and PEG conditions in order to evaluate the full genetic potential of NAM population against drought stress at seedling stage.Since improving the plant’s DT at early development can overcome the influence of soil water deficits and provide a solid base for obtaining high and stable yields.In Sand experiment,we applied water stress by withholding the water,while in case of PEG experiment;we used polyethylene glycol(PEG)as stress inducing agent to best evaluate the stress tolerance response among the lines in NAM.Later by using RTM-GWAS we dissected the parents and NAM genetic structure for DT.Our study therefore had the following main objectives;1)Development of favorable NAM population and clear indicators for DT workable for agronomy/plant breeding related research,2)Identification and analysis of the QTL-allele system for DT indicators both in Sand and PEG related experiments3)Prediction of breeding potential for DT indicators and4)Prediction of the candidate genes and elaboration of their putative functions.The main results are briefly presented below;1.Selection of the most suitable and major indicators for drought tolerance Several traits(morphological,physiological and growth related)have been used as a criteria to evaluate the DT of crops.However growth related ones are more important as these will finally be reflected in yield of crop.To select the most suitable and major indicators to evaluate DT,we developed a nested association mapping population(NAM).For that we selected nine soybean accessions from various resources.The relative plant length(RPL),shoot length(RSL),root length(RRL),plant dry weight(RPDW),root dry weight(RRDW)and shoot dry weight(RSDW)were evaluated for DT.We identified TongShan to be the most tolerant cultivar followed by ZengYang.The drought sensitive cultivar identified was M8206.Thus we selected these three parents to constitute a nested association mapping(NAM)population comprising of two recombinant inbred lines(RILs)populations i.e.,(M8206 x TongShan)and(ZengYang x M8206).Since the parent M8206 is common we refer this as ’MTZ’ NAM population.In the beginning we thought to select only one indicator for DT assessment,however our mapping results led us to conclude that for a complex trait like DT,only one indicator cannot cover it to its entirety.So we decided to select multiple indicators to be used as a set to study DT.In our present study out of relative plant length(RPL),relative root length(RRL),relative shoot length(RSL),relative plant dry weight(RPDW),relative root dry weight(RRDW)and relative shoot dry weight(RSDW),we identified RRL,RSL,and RPDW as a set of most appropriate and major indicators covering the major part of genome related to DT for Sand and PEG related breeding experiments.Heritability estimates and coefficient of variation(CV)were used as standard criteria for selecting the major indicators.As heritable variation is quite useful for permanent and sustainable genetic improvement and when combined with coefficient of variation(CV),could give much better picture of the success to be achieved through selection.In case of Sand experiment,higher heritabilities for RRL(83%)and for RSL(87%)with lower CV as 10.7%each for RRL and RSL respectively and collectively for both indicators 40 QTLs with 93 alleles accounting on an average of 34.74%of phenotypic variance(PV)led us to prefer these indicators over RPL whose heritability and CV values were 60 and 17.9%respectively with 21 detected QTLs with 48 alleles explaining 31.4%of PV.Similarly for RPDW indicator the heritability and CV were 91 and 12.4%respectively with 25 QTLs with 59 alleles detected explaining 45.95%of PV reasonably better that RRDW and RSDW each having 90%heritability and 15.5 and 16.2%CV respectively with detected 46 QTLs with 98 alleles explaining an average of 34.07%of PV collectively for RRDW and RSDW.In case of PEG experiment,for RRL the heritability and CV values were 85 and 11.4%respectively while for RSL these were 53 and 10.8%respectively and collectively for RRL and RSL,we detected 1 11 QTLs with 262 alleles explaining on an average of 33.27%of PV.While in RPL indicator we could only detect 28 QTLs accounting for 24.94%of PV.Obviously due to more comprehensive genome coverage by RRL and RSL,we preferred these as most appropriate indicators for further study.However among dry weight indicators,since RSDW was non-significant trait with much lower heritability(11%),so we only performed mapping for RPDW and RRDW indicators.QTLs detected for RPDW were 35 with higher 8.92%of PV than RRDW in which we also detected 35 QTLs with 7.04%of phenotypic contribution.Furthermore higher heritability and lower CV values for RPDW than RRDW made us to prefer RPDW over RRDW in case of PEG experiment.However in case of Sand experiment,for simplicity RPDW can be the most optimal indicator among the three for higher heritability and lower CV values and more number of QTL-alleles with greater PV explained followed by RSL and RRL.While for PEG experiment,we can select RRL to be more optimal and appropriate among other two indicators for most QTLs with greater PV,reasonably higher heritability estimates and lower CV values followed by RSL and RPDW.2.Identification and analysis of the QTL-allele system for drought tolerance indicators both in Sand and PEG experimentsThe ’MTZ’ NAM population comprising of 409 lines(285 lines from MT and 124 lines from ZM)was evaluated for DT under Sand and PEG experiments,and sequenced using RAD-seq to obtain 55,936 single nucleotide polymorphisms(SNPs)and organized into 6137 SNP linkage disequilibrium blocks(SNPLDBs)for GWAS.The genomic loci of SNPLDBs detected in this study were well distributed throughout the genome.The innovative restricted two stage multi-locus genome-wide association study(RTM-GWAS)identified 65 QTLs with 152 alleles with 38.48%of the phenotypic contribution and 146 QTLs with 341 alleles with 25.15%of the phenotypic contributions collectively for RRL,RSL and RPDW indicators under Sand and PEG experiments respectively.This result makes us understand that DT is a highly complex trait;different indicators had their own genetic regions owing to their own unique genetic systems.Only two regions were found to be common between Sand and PEG experiments.Out of a total of 211 QTLs with 493 alleles detected collectively for Sand and PEG experiments,as many as 13 QTLs with 31 alleles were happened to be exactly overlapped with those already reported in the literature(Soybase,the USDA Soybean Genome Database)and thus might be the same QTLs with pleiotropic effects.The remaining 198 QTL with 462 alleles are therefore the novel regions detected by the RTM-G WAS and are members of complex DT genetic system.Quantification of the genetic variation encompassing a whole crop genome constitutes a means to tap the stress tolerant loci.Thus the identified QTLs with their corresponding alleles for RRL,RSL and RPDW were organized into QTL-allele matrices,a compact form of genetic constitution of the population structure,thoroughly showing the DT genetic architecture of the three parents and the NAM population.All the lines were found to be an amalgamation of both positive and negative alleles indicating a great inherent recombination potential for breakthrough segregants in the population.Thus,the QTL-allele matrix can provide an approach in genotyping the parental materials and predicting the breeding values describing the superiority of individuals and thus the capability of transmitting the favorable alleles to their progenies.3.Breeding potential predictions among the three parents of NAM population and exploration of candidate gene system for drought toleranceFrom QTL-allele matrices,we found all the three parents(M8206,TongShan and ZengYang)had both positive and negative allele effects on the detected loci suggesting the possibility of predicting the best genotype(s)exists among them through collecting the favorable alleles in the progeny.Therefore comprehensive DT breeding potential of the three parents was predicted for each indicator that appeared to be greatly transgressive.Thereby the best alleles with corresponding allelic effects contributed by each parent were selected and added with the population mean value of the respective indicator and the breeding value for the best genotype was predicted with weighted average values(WAV)1.703 and 1.969 for Sand and PEG experiments respectively much higher than those of individual parents for the three indicators indicating much greater potential in achieving a best DT genotype through recombination and converging of the elite alleles.However due to high level of heterozygosity in the parents owing to their different sources of origin,to achieve that best genotype will take huge amount of segregations.Although the RILs are difficult to constitute as these take a long time to construct.But once established,due to their homozygous nature,the optimal cross selections can be made and benefitted to get the best genotype as close as the one predicted from the original parents.Therefore,83,436 potential single crosses were predicted from the 409 lines of NAM population.The predicted 95th percentiles linkage predictions and weighted average values(WAV)of the indicators for DT in progeny population served as the predicted ranges for comparisons among the crosses from which the top ten optimal crosses were selected indicating considerable potential for improvement in all indicators both in Sand and PEG experiments.The identification of potential candidate genes is critical for our understanding of physiological and molecular mechanisms for DT and enables us to use the transgenic technology in breeding.From the QTL system in NAM population,the candidate gene system was annotated based on Soybase.For all the three indicators,the association between the detected SNPLDBs and SNPs in the annotated genes was χ2-tested,and a DT related candidate gene system comprising of 107 genes with 27.19%of PV and 179 genes with 14.61%of PV inferred from Sand and PEG experiments respectively.Gene ontology(GO)enrichment analysis showed that the total 286 potential candidate genes conferring DT(107 and 195 genes in Sand and PEG experiments respectively)scattered throughout the genome and were found to be involved in various biological processes in the NAM.Eleven of the genes were found to be reported in the literature encoding proteins related to DT.Thus the remaining 275 candidate genes are the novel ones.The candidate genes sets detected along with their end products were unique for Sand and PEG experiments although the biological processes involved were similar between the two.These differences in candidate genes between Sand and PEG experiments might likely be due to their different nature of stress causing effects.These potential candidate genes were annotated in to nine GO categories of biological processes like ABA responders(Ⅰ),stress responders(Ⅱ),transporters(Ⅲ),development factors(Ⅳ),protein metabolism(V),transcription factors(Ⅵ),protein kinases(Ⅶ),unknown function(Ⅷ)and others(Ⅸ)indicating that diverse genes are involved and work in a cascade fashion in DT.Collectively for Sand and PEG experiments,the stress responder group(Ⅱ)was the largest one with 75 candidate genes involved.These might be the most likely candidates for DT.Transporters(Ⅲ)was next GO group composed of 51 candidate genes,and it potentially acts in multiple cellular transport processes which might help the plant to maintain an osmotic balance under drought by transporting osmolytes.It was followed by protein metabolism group(Ⅴ)having 47 genes.There were also some genes involved in development,transcription factors,protein kinases and ABA responders other groups(RNA methylation,DNA binding,photosynthesis etc).For both Sand and PEG experiments,for the three same indicators we detected different set of QTLs with different number of alleles and different set of candidate genes indicating the difference of genetic systems between the two methods.Although more number of QTLs(146 QTLs)as well as genes(179)were detected in PEG experiments than those in Sand with 65 QTLs and 107 genes for the three indicators,the phenotypic variances(PV)explained by the QTLs and genes detected in Sand(38.48 and 27.19%respectively)were greater than those detected in PEG experiments(25.15 and 14.61%respectively).Furthermore the heritability and CV values among indicators in Sand were better than those of in PEG experiments.It clearly indicates the genetic differences between the two methods employed to induce drought and also signifies that Sand related experiments using water withholding to induce drought are more closely related to natural drought than by that of using chemical like PEG in our case.However,owing to some share of DT related QTLs/genes,for simple and short experiments,we recommend that PEG can also be used to induce drought stress.To fully understand the complex gene system of DT,further fine mapping of detected QTLs for finding more precise QTLs and candidate gene verification thought different molecular biology experiments should be planned in future studies. |
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