Bioinformatic analysis of whole genome sequencing data

Evolution has shaped the life forms for billion of years. Domestication is an accelerated process that can be used as a model for evolutionary changes. The aim of this thesis project has been to carry out extensive bioinformatic analyses of whole genome sequencing data to reveal SNPs, InDels and selective sweeps in the chicken, pig and dog genome. Pig genome sequencing revealed loci under selection for elongation of back and increased number of vertebrae, associated with the NR6A1, PLAG1, and LCORL genes. The scan for copy number variations (CNVs) revealed four duplications at the KIT locus associated with dominant white and belt colour phenotypes. Selective sweeps in the dog genome included genes involved in adaptation to a starch rich diet, fat metabolism and behavior. Identification of a selective sweep and a CNV in the AMY2B gene, which correlates with variation in α-amylase expression, along with selective sweeps in MGAM and SGLT1, in dogs revealed adaptation to a starch-rich diet after domestication. Analysis of chicken genome resequencing data identified hundreds of regions under selection shared among all domestic chicken and others that were specific for layers or broiler chickens and 68 fixed large deletions and 70 small InDels in domestic chicken populations. Structural variations are changes in the genome that may affect the copy number of genes, their regulation or their coding sequence. Current methods utilize sequence information from either single sample or pair of samples to scan for CNVs across the genome. We developed a fast algorithm and a tool, MultiSV, to identify structural variations using short reads from massively parallel sequencing of multiple populations. This thesis demonstrates the importance of structural variations as a factor contributing to phenotypic diversity in domestic animals and has revealed regions under strong selection during animal domestication and breeding. It also presents a new method for the identification of structural variations in populations using short reads from NextGen sequencers