Identification of Transcript Polymorphisms for Seed Quality Improvement By Exploring Soybean Genetic Diversity

The difference in seed oil composition and content among soybean genotypes could be attributed mostly to variations in transcript sequences that change their protein functions and/or in transcript accumulation of oil-related genes expressed in seeds. We sequenced transcriptomes of soybean seeds from nine genotypes varying in oil composition and content. Having applied a wide range of bioinformatics algorithms, we identified a large collection of transcript polymorphisms including variations in transcript sequence (SNPs and indels), transcript accumulation and transcript splicing among the genotypes, and further predicted the transcript polymorphisms that potentially cause oil quality variation based on their biological effects. We successful rediscovered that the deletion of FAD2-1A gene and a non-synonymous SNP in FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41 respectively.  An effective algorithm was also developed to successfully predict several large DNA deletions.  We sequenced the genome and seed transcriptome of Jack, and compared their efficiency in discovering SNPs at various sequencing depth. Polymorphisms identified by this project could be developed into a set of functional markers for breeders to design effective crossing and marker assisted selection strategies for oil quality improvement. (The research is funded by the United Soybean Board and USDA-ARS)