Simplifications of marker-assisted genetic evaluation and accounting for non-additive interaction effects

Abstract

Abstract. A computing simplification was applied to marker-assisted genetic evaluation of quantitative traits including additive and non-additive effects of QTL as well as residual polygenic effects. Different situations including QTL and the residual polygenic effect estimated as a sum or separately, and with or without non-additive effects integrated in models were evaluated. The computing simplification was used in combinations with different models and parameterizations. An example data was adopted to illustrate the simplified computing strategy and was compared with the computing method of direct inversion. Identical results were obtained from both computing strategies. The main advantage of the simplification is that it does not require inversion of non-additive relationship matrices and relationship matrices of QTL, and the number of random effects in mixed model equations is the same as any animal model with only additive effects.