Linkage And Association Analysis And Candidate Gene Mining Of Hundred-seed Weight In Soybean

Hundred-seed weight(HSW)is an important measure of yield during soybean breeding,which is a complex quantitative trait affected by multiple genes and environmental conditions.To identify quantitative trait nucleotides(QTNs/QTLs)and mine genes useful for breeding high-yielding and high-quality soybean(Glycine max)cultivars,we used 144 four-way recombinant inbred lines(FW-RILs)as test materials,and performed phenotypic analysis on the HSW of soybean in 20 different environments.we obtained genotypic data for 109676 single nucleotide polymorphisms(SNPs)in 144 FW-RILs using a soybean 660 K chip.Five multi-locus genome-wide association study(GWAS)methods and linkage analysis method were used to identify QTNs/QTLs related to HSW of soybean in 20 different environments,and the candidate genes were predicted.The main results are as follows:1.Based on the SNP markers with high density,a genetic linkage map covering 20 chromosomes of soybean was constructed.The map contains 2,332 SNP markers,and the total length of 20 linkage groups is 3539.66 c M,the number of intervals is 1,031,the number of intervals smaller than 5c M is 835,and the coverage rate of soybean chromosomes is more than 90% in 17 chromosomes.2.Through the linkage analysis of soybean FW-RILs in 20 environments,51 QTLs of HSW were located,of which 13 QTLs were located by the permutation method,and 41 QTLs were located by the LOD value critical method,of which 3 QTLs were detected by two methods,and 2 QTLs were detected by the same method in different environments.3.Five Multi-locus GWAS methods named mr MLM,FASTmr MLM,FASTmr EMMA,p LARm EB and ISIS EM-BLASSO were used and 118 significant QTNs were located for HSW of soybean in 20 environments.By comparing the results of different methods,31 common QTNs were detected by two or more methods.4.We identified 20 large-seed lines with high HSW and 20 small-seed lines with low HSW based on the average phenotypic values of 144 FW-RILs in 20 environments.We found that the percentage of superior alleles of the large-seed lines was higher than that of the small-seed lines based on the information of the superior alleles of the 31 common QTNs.5.QTNs located by only one method in GWAS and QTLs located in linkage analysis were compared.The QTNs whose physical position coincides with the QTL were regarded as the common QTNs.Ten QTNs were found by combining GWAS and linkage analysis.6.Based on the QTL results mapped by linkage analysis,we selected 18 QTLs with the marker interval within 400 kb as specific QTLs to identify potential candidate genes.A total of 373 genes were found through bioinformatics,of which 76 genes were highly expressed in soybean seed.32 genes were annotated in 28 pathways and 3 protein families according to analysis of 76 gene pathways.Based on the annotation information of these genes and the functions in metabolic pathways,we judged three of them as potential candidate genes.7.Since the population we selected was not a natural group,but a four-way RIL population,the LD decay distance was very large.Therefore,the physical distance corresponding to the point where the decay rate is max and then tends to be gentle was used as the range of searching for candidate genes.As the LD decayed fastest before 200 kb and then tended to flatten,we searched for potential candidate genes at 100 kb intervals on either side of each QTN.We identified 635 genes in this interval,of which 129 were highly expressed during seed formation.Based on the annotation data,51 of the 129 genes were annotated in 29 pathways and three protein families in the KEGG database.Three of these are potential candidate genes based on their annotation information and function in metabolic pathways.The q RT-PCR method was used to analyze the expression levels of the three candidate genes.Among them,two candidate genes showed a significant difference in expression level between large and small HSW lines.8.As the LD decayed fastest before 200 kb and then tended to flatten,we searched for potential candidate genes at 100 kb intervals on either side of each common QTN.We eventually found 132 genes in this interval,of which 23 genes were highly expressed in seed formation.Based on gene annotation data,we found that 13 genes were annotated in 7 pathways and 3 protein families.Among them,we judge one of them as a potential candidate gene based on the annotation information of these genes and the functions in metabolic pathways.