Genomic evaluation considering the mosaic genome of the crossbred pig

In pigs, the breeding goal is to improve performance of crossbred (CB) animals in commercial farms. The best purebred (PB) animals to produce CB animals can be selected based on their genomic estimated breeding value (GEBV) for CB performance. GEBVs are the result of combining estimated effects of single nucleotide polymorphisms (SNPs) with the animal’s genotype. Using CB genomic information allows to estimate SNP allele effects accounting for the CB genetic background. The genome of CB animals is a mosaic of genomic regions inherited from the different parental breeds, therefore, this thesis aimed to investigate whether SNP alleles have different effects depending from which parental breed the allele was inherited and study the impact on GEBV of PB animals for CB performance when breed-specific allele effects were taken into consideration. Firstly, I showed that around 94 % of alleles of three-way CB pigs can be assigned a breed of origin. Knowing this, allowed me to implement a model that accounts for breed-specific effects of all SNP alleles. Using results of this model, I showed that estimated effects and explained variance of SNPs strongly associated with CB performance are different depending upon from which parental breed they were inherited, however, the majority of the genomic regions are not or only weakly associated with CB performance. Therefore, I implemented a new model that allows to estimate breed-specific effects only for alleles of SNPs strongly associated with CB performance, and for the rest of the SNPs assumes that allele effects are the same across breeds. Differences of prediction accuracies between models were generally small. When the estimated genetic correlation between the performance of PB and CB animals per breed of origin differed largely across models, it was better to use models that make a distinction of alleles according to their breed of origin and whether or not they were associated to the trait.