Submitted to: Cellular and Molecular Biology of Soybean Biennial Conference
Publication Type: Abstract Only
Publication Acceptance Date: May 15, 2012
Publication Date: August 1, 2012
Citation: Chen, P., Upchurch, R.G., An, Y. 2012. Identification of genes/loci and functional markers for seed oil quality improvement by exploring soybean genetic diversity [abstract]. Cellular and Molecular Biology of Soybean Biennial Conference. Available: http://www.osc.iastate.edu/mnet/soybean/level7.html. Technical Abstract: The difference in seed oil composition and content among soybean genotypes can be attributed mostly to variations in transcript sequences and/or transcript accumulation of oil-related genes expressed in seeds. We applied the Illumina HiSeq 2000 system to sequence RNA populations in soybean seeds from nine genotypes varying in profiles of lipid species and/or total oil content. For each genotype, an average of 35 million 100 bp paired-end reads were generated, and 30,167 annotated transcripts from 28,270 genes were detected in seeds at mid-maturation stage. A wide range of bioinformatic algorithms were used to determine the variation in transcript accumulation, transcript splicing, and transcript isoforms among the genotypes. Putative SNPs in those transcripts and indels in genes and genome segments were also identified. M23 is a previously characterized X-ray mutant line with a mid-oleic acid phenotype and has a deletion of a 160 kb genome segment encoding a delta-twelve fatty acid desaturase and 19 other proteins. We detected no or dramatically lower sequence reads aligning to those genes in M23 compared to the other genotypes, which validated the effectiveness of our approach. Pros and cons of this functional genomic approach to discover genes, gene variations and functional markers for seed oil quality improvement will be discussed in detail. Polymorphisms discovered by this project could potentially 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 supported by the United Soybean Board and USDA-ARS.