Moreover, Likelihood-based software for fitting mixed models with multiple random effects that allows the user to specify the variance-covariance structure of random effects has not been fully exploited. Mixed models have become a key tool for fitting genomic selection models, but most current genomic selection software can only include a single variance component other than the error, making hybrid prediction using additive, dominance and epistatic effects unfeasible for species displaying heterotic effects. Recently, genomic selection has earned attention as next generation sequencing technologies became feasible for major and minor crops. Most traits of agronomic importance are quantitative in nature, and genetic markers have been used for decades to dissect such traits.
