Location: Plant Genetics Research
Title: Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content Authors
Submitted to: Biomed Central (BMC) Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 7, 2014
Publication Date: April 23, 2014
Repository URL: http://handle.nal.usda.gov/10113/58745
Citation: Goettel, H.W., Xia, E., Upchurch, R.G., Wang, M.L., Chen, P., An, Y. 2014. Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content. Biomed Central (BMC) Genomics. 15:299. Interpretive Summary: Soybean represents the largest oil crop in the U.S. Soybean seed oil composition and content are important agronomic traits, determining its nutritional value as well as its utility for biodiesel production and other industrial applications. To identify genes, gene variants and highly effective markers that would allow soybean researchers to alter and improve these traits, we surveyed the expression of all genes active during soybean seed development. Genes, when active, first produce ribonucleic acid copies of themselves, termed transcripts and so to survey gene activity related to oil related processes we quantitatively sequenced the transcript populations in soybean seeds from nine lines varying in oil composition and/or total oil content. We determined that 50,485 distinct transcripts were expressed from 32,885 genes in seeds (some genes can produce more than one transcript). A total of 8037 transcript expression variants and 50,485 transcript sequence variants were identified among the genotypes. The effects of transcript variants (expression or sequence) on the protein sequences that they contain the code for and the functions the proteins might have in the seed were predicted. We obtained independent evidence confirming previous findings that the lack of the FAD2-1A gene activity or a mutant FAB2C gene results in elevated levels of the fatty acids oleic acid and stearic acid in the soybean lines, M23 and FAM94-4 respectively. We also observed an elevated transcript levels for genes clustered in a region of the genome of the Jack variety that is known to be involved in soybean cyst nematode resistance and that might prove useful as a marker for this trait in breeding strategies for disease resistance. The transcript variants we describe in this study are important for further oil related gene discovery efforts in soybean and for developing highly effective genetic markers for generation of new soybean germplasm with superior oil quality.
Technical Abstract: Genetic/genome diversity underlying variation in seed oil composition and content among soybean varieties can be largely depicted by differences in transcript sequences and/or transcript accumulation of oil producing related genes in seeds. In an effort to identify these variations, we sequenced transcriptomes of soybean seeds from nine lines varying in oil composition and/or total oil content. Our results showed that 50,485 distinct transcripts from 32,885 genes were expressed in seeds. A total of 8037 transcript expression polymorphisms and 50,485 transcript sequence polymorphisms (48,792 SNPs and 1693 small Indels) were identified among the lines. Effects of the transcript polymorphisms on their protein sequences and functionalities were predicted. We provided independent evidence that the lack of FAD2-1A gene activity and a non-synonymous SNP in the coding sequence of FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41, respectively. We also observed an elevated transcript accumulation of genes clustered at the rhg1 locus of soybean line Jack, suggesting their role in SCN-resistance in Jack. The collection of transcript polymorphisms coupled with their predicted functional effects presented in this study should be a valuable asset for further discovery of genes and gene variants important to oil qualities and for development of highly effective markers for soybean oil quality breeding programs.