The association of a given SNP with purebred (PB) performance might be different than its association with crossbred (CB) performance, because of interactions of the SNP marker with the environment or the genetic background. Therefore, the aim of the present study is to examine breed-specific associations of SNP to PB and CB performance. For this, we performed a genome-wide association study (GWAS) for back fat thickness (BF) with an approach that implements a genomic best linear unbiased prediction (GBLUP) model considering breed-of-origin of alleles. We observed some same regions for PB and CB performance, but the effects differed when observed in a PB or CB background. As expected, the breed with the lowest genetic correlation for BF between PB and CB, had fewest SNPs in common between PB and CB. Moreover, the effect of a given allele associated to BF in CB depended on the breed it was inherited from. These results suggest that SNP effects depend on the environment and on their genetic background, and are valuable to understand the low responses obtained when selecting PB animals for CB performance. The recognition of important regions associated to performance plus the differentiation of SNP effects according to their breed-of-origin, might inform future prediction models for CB performance. Keywords: crossbred, back fat thickness, pigs, linkage disequilibrium, gwas
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Electronic Poster Session - Methods and Tools - GWAS, , 332, 2018
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