Abstract Title

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

Abstract

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.

Modified Abstract

Latest advances in genotyping technologies 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, 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.

Research Category

Biology/Ecology

Primary Author's Major

Biochemistry

Mentor #1 Information

Dr. Helen Piontkivska

Presentation Format

Poster

Start Date

March 2016

Research Area

Bioinformatics

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Mar 15th, 1:00 PM

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.