Bayesian model combining linkage and linkage disequilibrium analysis for low density-based genomic selection in animal breeding

We combined linkage (LA) and linkage disequilibrium (LDA) analyses (emerging the term ‘LALDA’) for genomic selection (GS) purposes. The models were fitted to a simulated dataset and to a real data of feed conversion ratio in pigs. Firstly, the significant QTLs (quantitative trait locus) were identified through LA-based mixed models considering the QTL-genotypes as random effects by means of genotypic identity by descent matrix. This matrix was calculated at the positions of significant QTLs (based on LA) allowing to include the QTL-genotype effects additionally to SNP (single nucleotide polymorphism) markers (based on LDA) and additive polygenic effects in several GS models (Bayesian Ridge Regression – BRR; Bayes A – BA; Bayes B – BB; Bayes C – BC and Bayesian LASSO – BL). These models combing all mentioned effects were denominated LALDA. Goodness-of-fit and predictive ability analyses were performed to evaluate the efficiency of these models. For the real data, although slightly, the superiority ...