Including copy number variation in association studies to predict genotypic values

The objective of this study was to investigate, both empirically and deterministically, the ability to explain genetic variation resulting from a copy number polymorphism (CNP) by including the CNP, either by its genotype or by a continuous derivation thereof, alone or together with a nearby single nucleotide polymorphism (SNP) in the model. This continuous measure of a CNP genotype could be a raw hybridization measurement, or a predicted CNP genotype. Results from simulations showed that the linkage disequilibrium (LD) between an SNP and CNP was lower than LD between two SNPs, due to the higher mutation rate at the CNP loci. The model R2 values from analysing the simulated data were very similar to the R2 values predicted with the deterministic formulae. Under the assumption that x copies at a CNP locus lead to the effect of x times the effect of 1 copy, including a continuous measure of a CNP locus in the model together with the genotype of a nearby SNP increased power to explain variation at the CNP locus, even when the continuous measure explained only 15% of the variation at the CNP locus

A genome-wide linkage analysis for reproductive traits in F2 Large White × Meishan cross gilts

Female reproductive performance traits in pigs have low heritabilities thus limiting improvement through traditional selective breeding programmes. However, there is substantial genetic variation found between pig breeds with the Chinese Meishan being one of the most prolific pig breeds known. In this study, three cohorts of Large White × Meishan F(2) cross-bred pigs were analysed to identify quantitative trait loci (QTL) with effects on reproductive traits, including ovulation rate, teat number, litter size, total born alive and prenatal survival. A total of 307 individuals were genotyped for 174 genetic markers across the genome. The genome-wide analysis of the trait-recorded F(2) gilts in their first parity/litter revealed one QTL for teat number significant at the genome level and a total of 12 QTL, which are significant at the chromosome-wide level, for: litter size (three QTL), total born alive (two QTL), ovulation rate (four QTL), prenatal survival (one QTL) and teat number (two QTL). Further support for eight of these QTL is provided by results from other studies. Four of these 12 QTL were mapped for the first time in this study: on SSC15 for ovulation rate and on SSC18 for teat number, ovulation rate and litter size