After being transported into Europe during the Neolithic, mouflon (Ovis aries musimon) became extinct from mainland Europe, but remnant populations persisted and became feral on the Mediterranean islands of Corsica and Sardinia. These populations have been used for reintroductions across continental Europe during the last 200 years. This thesis aimed to investigate the global and local ancestry of European mouflon and domestic sheep, to investigate signals of artificial and natural selection in their genomes, and to develop analytical frameworks and informatic tools to aid similar analyses using SNP array data. I describe the development of software that allows rapid investigation of genome-wide SNP data to infer effective population size trajectories using patterns of linkage disequilibrium. I inferred the absence of widespread sheep introgression in extant European mouflon populations although signals of recent introgression were recorded in one enclosed Sardinian mouflon population. By applying a novel approach to aid the investigation of local genomic ancestry data, signals of mouflon ancestry in sheep could be inferred and were found to be related to biological functions involved with innate immunity processes with bitter taste recognition being identified in two breeds known for their broad dietary choices. By investigating signals of positive selection and local adaptation in feral and domestic sheep using novel locus-specific empirical p-value inference, traits with selection signatures such as fertility, pigmentation and behaviour were identified in sheep, while traits involved with stature - probably related to mating success - were found in mouflon. Signals of local adaptation to environmental variables were not detected, which is likely to be due to the inadequate sample available, determined by post-hoc analysis.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:683683 |
| Date | January 2016 |
| Creators | Barbato, Mario |
| Publisher | Cardiff University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://orca.cf.ac.uk/88872/ |
Page generated in 0.0021 seconds