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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Soybean Genomics & Improvement Laboratory » Research » Publications at this Location » Publication #387657

Research Project: Characterization of Genetic Diversity in Soybean and Common Bean, and Its Application toward Improving Crop Traits and Sustainable Production

Location: Soybean Genomics & Improvement Laboratory

Title: Genetic architecture of protein and oil content in soybean seed and meal

Author
item DIERS, BRIAN - University Of Illinois
item SPECHT, JAMES - University Of Nebraska
item GRAEF, GEORGE - University Of Nebraska
item Song, Qijian
item RAINEY, KATY - Purdue University
item RAMASUBRAMANIAN, VISHNU - Iowa State University
item LIU, XIAOTONG - University Of Minnesota
item MYERS, CHAD - University Of Minnesota
item STUPAR, ROBERT - University Of Minnesota
item An, Yong-Qiang - Charles
item BEAVIS, WILLIAM - Iowa State University

Submitted to: The Plant Genome
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/9/2023
Publication Date: 2/6/2023
Citation: Diers, B., Specht, J., Graef, G., Song, Q., Rainey, K.M., Ramasubramanian, V., Liu, X., Myers, C., Stupar, R., An, Y., Beavis, W. 2023. Genetic architecture of protein and oil content in soybean seed and meal. The Plant Genome. 16(1). Article e20308. https://doi.org/10.1002/tpg2.20308.
DOI: https://doi.org/10.1002/tpg2.20308

Interpretive Summary: Soybean is grown primarily for the protein and oil production and the crop accounted for 70% of the protein meal consumed worldwide. Improving soybean protein and oil contents in seeds and meals is becoming one of the major objectives in current soybean breeding programs. Previous studies have reported a number of DNA genomic regions that are associated with high seed protein content and oil content, but because the delimited regions are too wide and may harbor thousands of genes, determination of candidate genes of the traits is challenging. Scientists from universities and USDA-ARS developed a soybean population with 5,600 breeding lines that were grown in 10 environments over three years. Analysis of the DNA markers and trait data identified 64 genomic regions with genes for protein content and oil content in the seeds and/or meals, some of which are novel, and the span for most loci were much smaller than previously described. They also observed that the effects of these loci on the traits were generally small, suggesting that marker-assisted selection for these traits would likely be unsuccessful, and that genomic prediction would be a better approach. The results and resources will help scientists, soybean breeders, and geneticists working in the government, private industry, or at universities to further fine map or clone the genes and to develop an efficient strategy to improve soybean quality traits.

Technical Abstract: Soybean is grown primarily for the protein and oil extracted from its seed and the value of the crop is influenced by these components. The objective of this study was to map marker trait associations (MTAs) for the concentration of seed protein, oil, and meal protein using the soybean nested association mapping NAM population. Composition traits were evaluated on seed harvested from over 5,000 inbred lines of the SoyNAM population grown in 10 field locations across three years. Estimated heritabilities were at least 0.90 for all three traits. A negative correlation (-0.58) was estimated between seed oil and seed protein whereas a high positive correlation (0.92) was found between protein and meal protein. The lines were evaluated with SNP markers resulting in 107 marker-trait associations across the three traits. When MTAs that mapped within 5 cM of each other were binned. The total MTAs mapped to 64 loci on 19 of the 20 soybean chromosomes. Of the 64 MTAs, 37 were for protein content, 39 for meal protein and 31 for oil content. The effects for the majority of these MTAs were small. For cases where a protein and oil MTA mapped to the same interval, most (74%) had opposite effects for the two traits, consistent with the negative correlation between the traits.