Skip to main content
ARS Home » Midwest Area » Columbia, Missouri » Plant Genetics Research » Research » Publications at this Location » Publication #301112
Title: Identification of transcript polymorphisms for seed quality improvement by exploring soybean genetic diversity

Author
item An, Yong-Qiang - Charles
item Goettel, Herbert
item Upchurch, Robert
item Wang, Ming
item XIA, ERIC - University Of Illinois
item Liu, Zongrang
item CHEN, PENGYIN - University Of Arkansas

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 12/11/2013
Publication Date: 1/10/2014
Publication URL: https://pag.confex.com/pag/xxii/webprogram/Paper12951.html
Citation: An, Y., Goettel, H.W., Upchurch, R.G., Wang, M.L., Xia, E., Liu, Z., Chen, P. 2014. Identification of transcript polymorphisms for seed quality improvement by exploring soybean genetic diversity (abstract). Plant & Animal Genome. Paper No. 036.

Interpretive Summary:

Technical Abstract: The difference in seed oil composition and content among soybean genotypes could be mostly attributed to transcript sequence and/or expression variations of oil-related genes that that lead to changes in the functions of the proteins that they encode and/or their accumulation 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 used to further develop into a set of functional markers for breeders to design effective crossing and marker assisted selection strategies for oil quality improvement.