Association analysis using SSR and SNP loci to find QTL for seed oil content in soybean

Abstract

Association mapping will be used to identify genome regions and polymorphism of candidate genes that are associated with oil production and fatty acid composition in soybean populations. The mapping population will consist of two subpopulations of 48 soybean accessions each, one of which with high and the other subpopulation with low oil content. In order to confirm that these traits could be useful in a soybean breeding program, fatty acid compositions will be determined in each of the 96 individuals. Ali plants will be genotyped throughout the genome with 100 simple sequence repeat (SSR) markers, some of which will be selected based on their association with quantitative trait loci (QTL) for oil content and based on polymorphism shown in previous studies. Concurrently, we will sequence portions of up to 10 genes that are candidate loci involved with oil biosynthesis in a sample of 10 soybean accessions selected to high and low oil. The sequencing will lead to the identification of the single nucleotide polymorphisms (SNP) which developed into markers for those specific genes. SNPs that are causal of phenotypic variation will be priority for genotyping each of 96 individuals. Standardized disequilibrium coefficients (D') and squared allele-frequency correlations (r2) for pairs of SSR and SNP loci will be measured in order to estimated linkage disequilibrium. (LD). Detection of oil seed content will be done by testing for significant differences in allele frequencies between the low and high oil groups. Putative QTL may be identified on the basis of highly significant markers, becoming a useful tool in an oil breeding program to rapidly increased rates of genetic gains. (AU)