Genomic prediction of hybrid crops allows disentangling dominance and epistasis. Issue 1 (14th April 2021)

• Record Type: Journal Article
• Authors: González-Diéguez, David; Legarra, Andrés; Charcosset, Alain; Moreau, Laurence; Lehermeier, Christina; Teyssèdre, Simon; Vitezica, Zulma G
• Editors: Endelman, J B
• Is Part Of: Genetics. Volume 218:Issue 1(2021)
• Publication Date: 2021-04-14
• Subjects: dominance -- epistasis -- genetic variance -- heterosis -- genomic models -- genomic prediction -- GenPred -- shared data resources; Genetics -- Periodicals; 576.5
• DOI: 10.1093/genetics/iyab026
• Languages: English
• ISSNs: 0016-6731

Abstract

Abstract: We revisited, in a genomic context, the theory of hybrid genetic evaluation models of hybrid crosses of pure lines, as the current practice is largely based on infinitesimal model assumptions. Expressions for covariances between hybrids due to additive substitution effects and dominance and epistatic deviations were analytically derived. Using dense markers in a GBLUP analysis, it is possible to split specific combining ability into dominance and across-groups epistatic deviations, and to split general combining ability (GCA) into within-line additive effects and within-line additive by additive (and higher order) epistatic deviations. We analyzed a publicly available maize data set of Dent × Flint hybrids using our new model (called GCA-model) up to additive by additive epistasis. To model higher order interactions within GCAs, we also fitted "residual genetic" line effects. Our new GCA-model was compared with another genomic model which assumes a uniquely defined effect of genes across origins. Most variation in hybrids is accounted by GCA. Variances due to dominance and epistasis have similar magnitudes. Models based on defining effects either differently or identically across heterotic groups resulted in similar predictive abilities for hybrids. The currently used model inflates the estimated additive genetic variance. This is not important for hybrid predictions but has consequences for the breeding scheme— e.g. overestimation of the genetic gain within heterotic group. Therefore, we recommend using GCA-model, which is appropriate for genomic prediction and variance component estimation in hybrid crops using genomic data, and whose results can be practically interpreted and used for breeding purposes.