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Genome-Wide Association Study and Genomic Selection for Proteinogenic Methionine in Soybean Seeds

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dc.contributor.authorSinger, Williamen
dc.contributor.authorShea, Zacharyen
dc.contributor.authorYu, Dajunen
dc.contributor.authorHuang, Haiboen
dc.contributor.authorMian, M.A. Roufen
dc.contributor.authorShang, Chaoen
dc.contributor.authorRosso, Maria L.en
dc.contributor.authorSong, Qijan J.en
dc.contributor.authorZhang, Boen
dc.date.accessioned2023-04-18T17:54:51Zen
dc.date.available2023-04-18T17:54:51Zen
dc.date.issued2022-04-25en
dc.description.abstractSoybean [Glycine max (L.) Merr.] seeds have an amino acid profile that provides excellent viability as a food and feed protein source. However, low concentrations of an essential amino acid, methionine, limit the nutritional utility of soybean protein. The objectives of this study were to identify genomic associations and evaluate the potential for genomic selection (GS) for methionine content in soybean seeds. We performed a genome-wide association study (GWAS) that utilized 311 soybean accessions from maturity groups IV and V grown in three locations in 2018 and 2019. A total of 35,570 single nucleotide polymorphisms (SNPs) were used to identify genomic associations with proteinogenic methionine content that was quantified by high-performance liquid chromatography (HPLC). Across four environments, 23 novel SNPs were identified as being associated with methionine content. The strongest associations were found on chromosomes 3 (ss715586112, ss715586120, ss715586126, ss715586203, and ss715586204), 8 (ss715599541 and ss715599547) and 16 (ss715625009). Several gene models were recognized within proximity to these SNPs, such as a leucine-rich repeat protein kinase and a serine/threonine protein kinase. Identification of these linked SNPs should help soybean breeders to improve protein quality in soybean seeds. GS was evaluated using k-fold cross validation within each environment with two SNP sets, the complete 35,570 set and a subset of 248 SNPs determined to be associated with methionine through GWAS. Average prediction accuracy (r2) was highest using the SNP subset ranging from 0.45 to 0.62, which was a significant improvement from the complete set accuracy that ranged from 0.03 to 0.27. This indicated that GS utilizing a significant subset of SNPs may be a viable tool for soybean breeders seeking to improve methionine content.en
dc.description.sponsorshipThis research was supported by the United Soybean Board Grant Nos. 2120-152-0115 and 2220-152-0112.en
dc.description.versionPublished versionen
dc.format.extent13 pgen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationSinger WM, Shea Z, Yu D, Huang H, Mian MAR, Shang C, Rosso ML, Song QJ and Zhang B (2022) Genome-Wide Association Study and Genomic Selection for Proteinogenic Methionine in Soybean Seeds. Front. Plant Sci. 13:859109. doi: 10.3389/fpls.2022.859109en
dc.identifier.doihttps://doi.org/10.3389/fpls.2022.859109en
dc.identifier.urihttp://hdl.handle.net/10919/114547en
dc.identifier.volume13en
dc.language.isoenen
dc.publisherFrontiersen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectsoybean proteinen
dc.subjectsoybean amino aciden
dc.subjectmethionineen
dc.subjectsulfur-containing amino aciden
dc.subjectGWASen
dc.subjectgenomic selectionen
dc.titleGenome-Wide Association Study and Genomic Selection for Proteinogenic Methionine in Soybean Seedsen
dc.title.serialFrontiers in Plant Scienceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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