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United States Department of Agriculture

Agricultural Research Service

Research Project: BIOINFORMATIC METHODS AND TOOLS TO PREDICT SMALL GRAIN FIELD PERFORMANCE

Location: Plant, Soil and Nutrition Research

Title: Plant breeding with genomic selection: potential gain per unit time and cost

Authors
item Heffner, Elliot -
item Lorenz, Aaron
item Jannink, Jean-Luc
item Sorrells, Mark -

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 1, 2010
Publication Date: July 1, 2010
Citation: Heffner, E.L., Lorenz, A.J., Jannink, J., Sorrells, M.E. 2010. Plant breeding with genomic selection: potential gain per unit time and cost. Crop Science. 50:1681-1690.

Interpretive Summary: Advances in genotyping are rapidly decreasing DNA marker costs and increasing our ability to cover the complete genome with markers. This is facilitating the use of marker-assisted selection (MAS) in plant breeding. Commonly employed MAS strategies, however, are not well suited for complex traits, requiring extra time for field-based phenotyping to identify agronomically superior lines. Genomic selection (GS) is an emerging alternative to MAS that uses all marker information to predict performance for complex traits. Selections can be made on performance predictions without further phenotyping. We developed an analytical framework to compare gains from MAS and GS for complex traits and to provide a plant breeding context for interpreting results from studies on how accurately GS predicts performance. We designed MAS and GS breeding strategies with equal budgets for a high-investment maize program and a low-investment winter wheat program, and analyzed expected gains from selection using our framework. Results indicate that GS can outperform MAS on a per year basis even if performance predictions are not highly accurate. We conclude that if moderate selection accuracies can be achieved, GS could dramatically accelerate genetic gain through its shorter breeding cycle.

Technical Abstract: Advancements in genotyping are rapidly decreasing marker costs and increasing genome coverage. This is facilitating the use of marker-assisted selection (MAS) in plant breeding. Commonly employed MAS strategies, however, are not well suited for complex traits, requiring extra time for field-based phenotyping to identify agronomically superior lines. Genomic selection (GS) is an emerging alternative to MAS that uses all marker information to calculate genomic estimated breeding values (GEBVs) for complex traits. Selections are made directly on GEBV without further phenotyping. We developed an analytical framework to: 1) compare gains from MAS and GS for complex traits and 2) provide a plant breeding context for interpreting results from studies on GEBV accuracy. We designed MAS and GS breeding strategies with equal budgets for a high-investment maize program and a low-investment winter wheat program. Results indicate that GS can outperform MAS on a per year basis even at low GEBV accuracies. Using a previously reported GEBV accuracy of 0.53 for net merit in dairy cattle, expected annual gain from GS exceeded that of MAS by about 3-fold for maize and 2-fold for winter wheat. We conclude that if moderate selection accuracies can be achieved, GS could dramatically accelerate genetic gain through its shorter breeding cycle.

Last Modified: 9/2/2014
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