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

Author:

Diers Brian W.1ORCID,Specht James E.2,Graef George L.2ORCID,Song Qijian3,Rainey Katy Martin4,Ramasubramanian Vishnu5ORCID,Liu Xiaotong6,Myers Chad L.7,Stupar Robert M.8ORCID,An Yong‐Qiang Charles9,Beavis William D.5

Affiliation:

1. Department of Crop Sciences University of Illinois Urbana IL USA

2. Department of Agronomy and Horticulture University of Nebraska Lincoln NE USA

3. Soybean Genomics and Improvement Laboratory, USDA‐ARS Beltsville MD USA

4. Department of Agronomy Purdue University West Lafayette IN USA

5. Department of Agronomy Iowa State University Ames IA USA

6. Bioinformatics and Computational Biology Graduate Program University of Minnesota – Twin Cities Minneapolis MN USA

7. Department of Computer Science and Engineering University of Minnesota – Twin Cities Minneapolis MN USA

8. Department of Agronomy and Plant Genetics University of Minnesota St. Paul MN USA

9. USDA‐ARS Plant Genetic Research Unit at Donald Danforth Plant Science Center St. Louis MO USA

Abstract

AbstractSoybean is grown primarily for the protein and oil extracted from its seed and its value 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 (SoyNAM) population. The composition traits were evaluated on seed harvested from over 5000 inbred lines of the SoyNAM population grown in 10 field locations across 3 years. Estimated heritabilities were at least 0.85 for all three traits. The genotyping of lines with single nucleotide polymorphism markers resulted in the identification of 107 MTAs for the three traits. When MTAs for the three traits that mapped within 5 cM intervals were binned together, the MTAs were mapped to 64 intervals on 19 of the 20 soybean chromosomes. The majority of the MTA effects were small and of the 107 MTAs, 37 were for protein content, 39 for meal protein, and 31 for oil content. For cases where a protein and oil MTAs mapped to the same interval, most (94%) significant effects were opposite for the two traits, consistent with the negative correlation between these traits. A coexpression analysis identified candidate genes linked to MTAs and 18 candidate genes were identified. The large number of small effect MTAs for the composition traits suggest that genomic prediction would be more effective in improving these traits than marker‐assisted selection.

Funder

National Institute of Food and Agriculture

United Soybean Board

Publisher

Wiley

Subject

Plant Science,Agronomy and Crop Science,Genetics

Reference68 articles.

1. Identification of Quantitative Trait Loci (QTL) Underlying Protein, Oil, and Five Major Fatty Acids’ Contents in Soybean

2. American Soybean Association(2019). 2019 SoyStats.https://soygrowers.com/wp‐content/uploads/2019/10/Soy‐Stats‐2019_FNL‐Web.pdf

3. Soybean [Glycine max (L.) Merr.] Breeding: History, Improvement, Production and Future Opportunities

4. Nested Association Mapping of Stem Rust Resistance in Wheat Using Genotyping by Sequencing

5. Beavis W. D.(1994).The power and deceit of QTL experiments: Lessons from comparative QTL studies.Proceedings of the Forty‐ninth Annual Corn and Sorghum Research Conference(pp250–266).American Seed Trade Association.

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