QTL Mapping And Candidate Gene Prediction Of Yield Related Traits In Soybean

Soybean,as one of the important global oil and protein crops,its yield formation is closely related to grain traits and other agronomic traits.It has become increasingly difficult to improve soybean yield related traits using traditional breeding methods,and using molecular breeding techniques to cultivate high-yield soybean varieties has become one of the emerging main breeding methods.In order to improve the efficiency of soybean breeding,accelerate the process of high-yield breeding,explore yield related loci,and apply them in molecular marker assisted selection,it has received increasing attention from breeders.This study used soybean varieties Jiyu 93 and Nematode resistant 6 as parents to construct F₂populations and their derived F₃populations(i.e.F_2:3populations)as experimental materials.SNP markers were obtained through sequencing to construct high-density linkage maps.Finally,based on the phenotype of the materials,a complete interval mapping method was used to locate QTLs for pods per plant,grains per plant,grain weight per plant,and 100 grain weight per plant.Candidate genes were screened for intervals based on the Soy Base database.The main research conclusions are as follows:Firstly,there were significant differences in grain number per plant and 100 grain weight between the two parents in the F₂generation population,while there were significant differences in grain number per plant,grain weight per plant,and 100 grain weight between the F_2:3population.The yield correlation between the two populations showed varying degrees of segregation and hyperparency compared to the two parents.Combining the relevant data of the two populations’traits,it was found that the number of grains per plant,grain weight,pod number,and 100 grain weight were in line with the inheritance characteristics of quantitative traits controlled by multiple gene interactions.In addition,there was a highly significant correlation between the number of grains per plant and grain weight within the study materials,indicating a certain degree of overlap in their genetic basis.Secondly,1634 high-quality SNP markers were screened through SNP sequencing,and based on these loci,Ici Mapping was applied to construct a genetic linkage map with a total length of 4298.30c M.This map covers 20 pairs of chromosomes,with an average number of markers per chromosome of 81.7.The average distance between markers is 1.80-6.77c M,and the maximum gap is between 12.61-59.59c M.Among them,chromosome 2 has the most SNP markers（155）;Chromosome 20 has the least number of markers（24）.Although the distribution of SNP loci on chromosomes varies and there is a significant difference,the average distance between markers is small,so this map can meet the needs of QTL localization.Thirdly,with LOD=2.5 as the threshold,a total of 48 QTLs related to the target trait were identified using ICIM and CIM methods in F₂and F_2:3populations.Among them,QTL（q-21-15-PN-1）,QTL（q-2020-17-SN-1,q-2020-18-SN-1）,and QTL related to 100 grain weight（q-2020-1-HSW-1）were identified by two methods and can be stably detected in both populations.Eight and 34 QTL loci were identified in the F₂population using ICIM and GCIM methods,respectively.Six QTL loci were identified in the F_2:3population using ICIM methods,and were distributed on the remaining 17 chromosomes except for staining 4,7,and 11,including three relatively dominant QTLs.The F₂population adopts the ICIM method,which includes detecting 2 QTL loci in the number of pods per plant,with phenotypic contribution rates ranging from 0.53 to 4.74%;Three QTL loci were detected in the number of grains per plant,with phenotypic contribution rates ranging from 0.73%to 7.73%;Two QTL loci were found in the single plant grain weight,with phenotypic contribution rates ranging from 2.28%to2.32%;One QTL locus was detected in 100 grain weight,with a phenotypic contribution rate of5.22%;In chromosome 9,q-2020-9-PN-1 overlaps with q-2020-9-SW-1 and q-2020-9-SN-1 in physical intervals（20218437-49893816bp）.Therefore,it can be inferred that the population used in this study may have genes that jointly control the number of pods per plant,grain weight per plant,and grain number per plant on chromosome 9.The contribution rate of 6 loci related to the number of pods per plant detected by GCIM method is 2.27%;Eight loci related to individual plant grain weight were detected,with the highest contribution rate of 1.59%;Nine loci related to grain size per plant were detected,with the highest contribution rate of 2.73%;Eleven loci related to 100 grain weight were detected,with the highest contribution rate of2.00%.Both methods detected 100 grain weight related loci on chromosome 1,and the ICIM and GCIM methods detected the same loci.Three QTL loci were detected in the F2:3 population using the ICIM method,with a LOD of 2.5 as the threshold for the number of pods per plant.The phenotypic contribution rate ranged from 4.80%to 5.34%;One QTL locus was detected in the number of grains per plant,with a phenotypic contribution rate of 5.61%;One QTL locus was found in the grain weight of a single plant,with a phenotypic contribution rate between 2.83%;Three QTL loci were detected in 100grain weight,with phenotypic contribution rates ranging from 2.60 to 3.27%.Fourthly,7175 genes were found within the mapping interval of the 48 QTLs identified above.Screening candidate genes related to soybean pods per plant,grains per plant,grain weight per plant,and 100 grain weight through Go annotation,A total of 47 candidate genes were screened through Go annotation for candidate genes related to target traits（Glyma09g24410、Glyma09g25110、Glyma09g25830、Glyma09g27410、Glyma09g28140、Glyma09g28930、Glyma09g30910、Glyma09g31730、Glyma09g35050、Glyma09g35170、Glyma09g36080、Glyma09g36830、Glyma09g36850、Glyma09g36940、Glyma09g38140、Glyma09g38500、Glyma09g38570、Glyma09g39610、Glyma09g39660、Glyma09g41460、Glyma13g00280、Glyma13g01150、Glyma13g01440、Glyma13g01570、Glyma13g05380、Glyma13g06730、Glyma13g18120、Glyma13g18450、Glyma13g19290、Glyma13g33290、Glyma13g33300、Glyma13g33890、Glyma13g36180、Glyma17g06280、Glyma17g07450、Glyma17g07570、Glyma17g07690、Glyma17g07700、Glyma17g09110、Glyma17g09390、Glyma17g35530）,among which 10 candidate genes are highly expressed in flowers.There are three candidate genes that are highly expressed in the correlation between the number of pods per plant,There are 34 candidate genes that are highly expressed at each developmental stage of each seed.The results of gene annotation,classification statistics and enrichment analysis within the QTL interval showed that most of the genes involved in annotation were related to flower growth,cell metabolism,cell growth,cell differentiation,carbohydrate metabolism,biosynthesis technology,and multicellular organism development.The gene Glyma09g41460,which is highly expressed in pods,is associated with lipid binding;The gene Glyma13g18450GO,which is highly expressed in grains,is annotated as related to the intimal system,nutrient reserve activity,and abscisic acid stimulation activity,which may increase the accumulation of nutrients in grains through these three ways,thereby increasing the quantity and weight of grains.