Bioinformatics analysis of single nucleotide polymorphisms (SNPs) in genes linked to exercise performance

Latest advances in genotyping technologies, including data from numerous genome-wide association studies, resulted in large quantities of human genomic data available for analysis of complex phenotypes. During the last decade search for the genetic factor underlying exercise performance-related phenotypes led to identification of multiple genetic candidates (Bray, Hagberg et al. 2009). However, because performance phenotype is a complex multifactorial trait, our understanding of molecular mechanisms underlying exercise performance is still limited. In this study we will examine distribution of SNPs from a set of genes that belong to the same genomic pathways as known candidate genes implicated in exercise phenotypes. The purpose of this study is to identify a subset of genes with the highest density of nonsynonymous and/or splice junction SNPs that will serve as the most likely gene candidates for future exome study linking genetic polymorphisms with endurance exercise.