Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.
Though epistasis has long been postulated to have a critical role in genetic regulation of important pathways as well as provide a major source of variation in the process of speciation, the importance of epistasis for genomic selection in the context of plant breeding is still being debated. In this paper, we report the results on the prediction of genetic values with epistatic effects for 280 accessions in the Nebraska Wheat Breeding Program using adaptive mixed least absolute shrinkage and selection operator (LASSO). The development of adaptive mixed LASSO, originally designed for association mapping, for the context of genomic selection is reported. The results show that adaptive mixed LASSO can be successfully applied to the prediction of genetic values while incorporating both marker main effects and epistatic effects. Especially, the prediction accuracy is substantially improved by the inclusion of two-locus epistatic effects (more than onefold in some cases as measured by cross-validation correlation coefficient), which is observed for multiple traits and planting locations. This points to significant potential in using non-additive genetic effects for genomic selection in crop breeding practices.
Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE 68583, USA. dwang3@unl.edu
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D
Wang
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Salah El-Basyoni
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Stephen Baenziger
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Crossa
K M
KM
Eskridge
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Dweikat
D001947:Breeding; D004843:Epistasis, Genetic / Q000502:physiology*; D018745:Genome, Plant / Q000502:physiology*; D008957:Models, Genetic; D010944:Plants / Q000235:genetics*; D019655:Quantitative Trait, Heritable