Use of genetic markers in pig breeding programs

The objective of this thesis was to investigate the use of genetic markers in commercial pig breeding, with a special emphasis on genomically imprinted genes. For the latter purpose, an association study was undertaken to identify genomically imprinted QTL related to sow fertility traits in two commercial pig populations. Furthermore, several simulation studies were performed to evaluate methods to estimate breeding values with marker data. Finally, a new method was designed to estimate the parental origin of marker alleles in crossed populations when the pedigree is unknown.

The association study involved approximately sows from two commercial pig populations. The sows were genotyped for SNP markers, of which were finally used. The results revealed one SNP with a significant imprinting effect on the trait litter size in one population. The imprinting effect of this SNP was not significant in the other population but its effect was similar. The SNP was located close to the gene DIO3, which has a known imprinting status. Furthermore, several SNP with significant additive and dominance effects were found in both populations.

The simulation studies were designed to evaluate the effect of the number of genes and the relative importance of these genes on the trait on performance of distinct methods to estimate breeding values with markers. Results of the first study showed that the performance of these methods is affected by gene number and size. Results of the second study continued on these results and showed that genetic gain achievable by selecting on breeding values estimated by these methods strongly depends on the number of genes and their relative size.

Knowledge of parental origin of marker or gene alleles is of crucial importance to study genomically imprinted genes. A method based on the Dirichlet Process was designed to estimate the parental origin of SNP alleles in crossed populations. The method performed better than methods that did not account crossbreeding, and the performance of the method was strongly improved when some genotypes of some parental individuals were available in the data.

The last chapter evaluated the influence of genomic imprinting on genetic parameters of genes. An important conclusion of this chapter is that genomically imprinted genes have less variance compared to similar, non-imprinted genes. This lower variance leads to lower power of statistical methods to detect these genes and lower genetic gain achievable in breeding programs. On the other hand, however, genomically imprinted genes could be effectively used in crossbreeding programs.