Expression Quantitative Trait Loci (eQTL) Mapping of Seed Composition, Seed Size, and Yield in Soybean Using Recombinant Inbred Lines (RILs).

Oil from soybean (biodiesel) represents a very attractive source of renewable energy. In order to make biodiesel production from soybean more economically advantageous, it is critical to breed for soybean cultivars high in oil and yield. To achieve this goal, a better understanding of the genetic mechanisms controlling seed composition and yield is needed. Traditionally, quantitative trait loci (QTL) mapping has been used to identify genetic loci that are associated with traits of interest. However, this method has significant limitations. This project employs a genomics strategy that involves identification of expression quantitative trait loci (eQTL) that control variations in gene expression between different soybean cultivars. As differences in gene expression are believed to be responsible for much of the phenotypic variability between these cultivars, eQTL are likely to play a critical role in regulating phenotypic variability. To identify eQTL, a population of recombinant inbred lines (RILs) that differ in seed yield, oil and protein content and seed size were developed from the Minsoy and Archer soybean cultivars. To identify genes that are expressed at different levels in the RILs, seeds were harvested from two RILs and both parental lines at three different developmental stages. Gene expression profiling was then performed using the Affymetirx GeneChip Soybean Genome Array, which contains information from approximately 37,500 soybean transcripts. The raw fluorescence data were preprocessed by GCRMA after quality control analysis in Bioconductor in the R environment. The resulting expression data were then analyzed using the limma function moderated by the empirical Bayes method in combination with Benjamini-Hochberg’s False Discovery Rate (FDR) to identify genes that are differentially expressed between the two RILs and the parents. Based on these results, approximately 550 differentially expressed genes will be selected for analysis in additional RILs using Illumina BeadChip arrays. Association analysis of the variations of the expression levels of these 550 genes and the known segregation patterns of molecular markers in the RILs will be used to identify eQTL controlling variations in gene expression and therefore, variations in seed composition and yield.