Electrical and Computer Engineering, Industrial and Manufacturing Systems Engineering, Bioeconomy Institute (BEI)
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Genomic selection is a technique that breeders use to select plant or animal individuals to mate and produce new generations of species. The conventional selection method is to select individuals that are either observed or predicted to be the best based on the assumption that parents with better phenotypes will produce better offspring. A major limitation of this method is its focus on the short‐term genetic gains at the cost of genetic diversity and long‐term growth potential. Recently, several new genomic selection methods were proposed to maximize the long‐term potential. Along this research direction, we propose a new method, the complementarity‐based selection strategy (CBS), to improve the tradeoff between short‐term genetic gain and long‐term potential. This approach is inspired by the genetic compatibility mate‐choice mechanism in animals. Our selection method selects the individual with the highest genomic estimated breeding value to emphasize short‐term achievement and then pairs it with the individual that is the most complementary to the one with highest genomic estimated breeding value to emphasize the long‐term growth potential. The CBS method allows favorable alleles to be accounted for within the selection and more of them to be included. We present simulation results that compare the performance of the new method against the state‐of‐the‐art methods in the literature and show that the CBS approach has a great potential to further improve long‐term response in genomic selection.
The Authors. Crop Science. Crop Science Society of America.
Moeinizade, Saba; Wellner, Megan; Hu, Guiping; and Wang, Lizhi, "Complementarity‐based selection strategy for genomic selection" (2020). Industrial and Manufacturing Systems Engineering Publications. 236.