Genetic Dissection Of The Relationship Between Biomass And Yield Component Traits In Soybean(Glycine Max(L.)Merr.) By Association Analysis

Soybean(Glycine max(L)Merrill)is in use for more than 5000 years in China and South East Asia as food and with its countless and varied uses,is an important crop at the global level.Its seeds are rich in oil(approximately 20%)and protein(approximately 40%).Although the soybean was originated in China,the soybean yield in China is very low.The main reasons for this are that the scale of soybean cultivated by farmers is small and,therefore,advanced cultural practices have not been adopted.The demand for soybean in China is increasing rapidly and the domestic production cannot meet these demands and China is importing soybean to fulfill this demand,becoming now the largest soybean importer country in the world.Thus,it is important to find tools which can faster the improvement of soybean yield in China,and as a result the aforementioned demands can be decreased and also the importation of soybean in turn.The improvement of soybean yield using traditional approach is becoming much difficult.However,many alternatives tools have been provided by the development of genomics in order to improve breeding efficiency.Linkage analysis is used to identify the genetic causative loci which control base traits.Several quantitative traits loci(QTLs),responsible for important agronomic traits have been identified by the use of linkage mapping.However,traditional bi-parent segregation populations used in linkage mapping have revealed several disadvantages,including limited genetic variation,low-density markers(100-200 markers)and mapping resolution.An alternative to linkage mapping is Association Mapping(AM),which is a new powerful tool to identify the location of gene(s)/allele(s)of interest.Relying on the strength of associations between genetic markers and phenotype among unrelated individuals,association mapping has the power to identify a single nucleotide polymorphisms(SNP)within a gene that is responsible for diverse phenotype.In soybean breeding,high-yield and stable-yield is the main goal,but yield is a complex quantitative trait which is easily affected by environment.Therefore,only QTLs that express stability in different populations and environments are of great value for soybean breeding.Biomass,one of the main factors that determine the effective economic yield,has an important effect on the final seed Yield.According to previous research,good results have been achieved by coordinating different yield components and biomass to the seed yield improvement in soybean,indicating that there is ample room for further yield improvement by genetic means.Therefore,we conducted this study which the main goal was to identify the genetic relationships between biomass traits and yield component traits in soybean accessions and to detect the SNPs that are responsible for these traits by genome wide association study(GWAS).For the experiment on the evaluation procedure,a set of 219 accessions include 210 accessions from China covering 24 provinces which covered four ecological regions and 7 accessions from USA,one from Japan and one from Brazil were used.Investigating study was done from 2013 to 2014 at Jiangpu Experimental Station of Nanjing Agricultural University,located in Nanjing,in a randomized block design with three replications under natural conditions.Six traits were characterized phenotypically under two environments including fresh biomass,dry biomass,total pods per plant,100-seed weight,total seeds per plant and seed yield.Four samples of above-ground plant were harvested after achieved the R6 stage for measurements of both fresh and dry biomass traits and other four samples were also harvested after achieved the full maturity(R8)for measurements of yield component traits(total pods per plant,100-seed weight,total seeds per plant and seed yield).For the genotyping,1142 SNP molecular markers covering the 20 chromosomes of soybean genome were used to screen the 191 soybean accessions out of 219 accessions.TASSEL 3.0 software based on Mixed Linear Model(MLM)was used to identify associations between markers and traits and the R software were used for statistical analyses of all phenotypic data.The analysis revealed highly significant positive correlations between biomass traits with pods per plant as well as a significant moderate high correlation with seed yield compared with other yield component traits,demonstrating that the soybean seed yield raises more with biomass.A total of 37 SNP-trait associations were identified and among these,23 SNPs were detected in one environment and each one of these associated with a single trait(including all traits).3 SNPs were identified in two environments co-associated with two traits,BARC-041167-07925 associated with 100-seed weight and total seeds per plant,BARC-040407-07733 associated with 100-seed weight and total seeds per plant,and BARC-017179-02234 was associated with total pods per plant and total seeds per plant;BARC-038885-07387 in one environment was co-associated with two traits(total pods per plant and total seeds per plant);BARC-014927-01924 in two environments was associated with a 100-seed weight.The elite alleles were mined for thirty-seven distinct SNPs by the mean value of the allele based on the means of the phenotypic values of each trait in both environments.Furthermore,thirteen typical carrier materials harboring the elite alleles were also mined.These mined elite alleles may provide a theoretical basis for genetic analysis of biomass and yield component traits and may faster marker-assisted selection(MAS)breeding in soybean.