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

William M Singer; Zachary Shea; Dajun Yu; Haibo Huang; M A Rouf Mian; Chao Shang; Maria L Rosso; Qijan J Song; Bo Zhang

doi:10.3389/fpls.2022.859109

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

Front Plant Sci. 2022 Apr 25:13:859109. doi: 10.3389/fpls.2022.859109. eCollection 2022.

Authors

William M Singer¹, Zachary Shea¹, Dajun Yu², Haibo Huang², M A Rouf Mian³, Chao Shang¹, Maria L Rosso¹, Qijan J Song⁴, Bo Zhang¹

Affiliations

¹ School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, United States.
² Department of Food Science and Technology, Virginia Tech, Blacksburg, VA, United States.
³ Soybean and Nitrogen Fixation Unit, United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Raleigh, NC, United States.
⁴ Soybean Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Beltsville, MD, United States.

Abstract

Soybean [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 (r ²) 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.

Keywords: GWAS; genomic selection; methionine; soybean amino acid; soybean protein; sulfur-containing amino acid.