Detection and mapping of quantitative trait loci in domestic farm livestock species

With the rapid development of both marker and computer technology many attempts are being made to identify regions of the genome associated with variation in quantitative traits. These regions are named quantitative trait loci (QTLs). Identifying QTLs within the porcine genome is of considerable scientific and commercial interest as findings could lead to the cloning of genes and the improvement of livestock through marker assisted selection or introgression. The aims of the thesis were to investigate, by simulation, various aspects of the QTL mapping method and apply the methods to scan the porcine genome for QTLs. Methods of constructing confidence intervals were investigated by simulation. Confidence intervals were created using a non-parametric (resampling method) and parametric (resimulation method) bootstrap. The non-parametric bootstrap performed well overall and produced results close to expectation when the QTL was not at a marker location but confidence intervals when the QTL was at a marker location were conservative. The parametric method performed poorly; results varied from conservative confidence intervals at the location of a marker, to anti-conservative intervals midway between markers. The results were shown to be influenced by a bias in the mapping procedure and by the accumulation of type I errors at the location of markers. The mapping of the porcine genome was achieved using a Meishan x Large White F 2 population. These breeds were chosen because they differed significantly for several traits of economic interest. Markers covered approximately 85% of the porcine genome and animals were measured for growth and fatness traits. Chromosomes 4, 7 and 14 had a genome wide significant effect on at least one trait. In all cases the single gene model was significantly better than the polygenic model. The effects on chromosome 4 for growth were in agreement with previous studies notably a similar study using wild boar from Sweden. Chromosome 7 had a large effect on fatness (over 6mm between breeds) and is of considerable interest because the Large White carries the alleles for high fat depth. Chromosome 14 was shown to have a significant effect on growth rate on test. Confidence intervals were produced by the non-parametric bootstrap and were found to be relatively large (in excess of 30cM) for the locations on chromosomes 4 and 14. In contrast the confidence intervals on chromosome 7 were smaller and corresponded to the major histocompatibility complex, a very gene rich region of the genome. Chromosome 4 data were also collected from other participating members of the PiGMaP consortium. The data were analysed individually and collectively. The data from all populations showed an effect on growth, the effect on fatness varied between populations. Only the French population showed evidence for an effect on birth weight. Confidence intervals for the position of the effects remained large, which was partly due to lack of uniformity in the data recorded between different populations. These analyses were the largest QTL studies ever achieved with livestock and demonstrate the potential benefits of combining information.