Mar 31, 2012

Prioritization of SNPs for genome-wide association studies using an interaction model of genetic variation, gene expression, and trait variation

Molecules and Cells
Hyojung PaikDoheon Lee

Abstract

The identification of true causal loci to unravel the statistical evidence of genotype-phenotype correlations and the biological relevance of selected single-nucleotide polymorphisms (SNPs) is a challenging issue in genome-wide association studies (GWAS). Here, we introduced a novel method for the prioritization of SNPs based on p-values from GWAS. The method uses functional evidence from populations, including phenotype-associated gene expressions. Based on the concept of genetic interactions, such as perturbation of gene expression by genetic variation, phenotype and gene expression related SNPs were prioritized by adjusting the p-values of SNPs. We applied our method to GWAS data related to drug-induced cytotoxicity. Then, we prioritized loci that potentially play a role in druginduced cytotoxicity. By generating an interaction model, our approach allowed us not only to identify causal loci, but also to find intermediate nodes that regulate the flow of information among causal loci, perturbed gene expression, and resulting phenotypic variation.

  • References43
  • Citations1

Mentioned in this Paper

Genome-Wide Association Study
Candidate Gene Identification
Gene Expression
Cytotoxicity
Nucleotides
Observation Method - Cytotoxicity
Deviation, Epistatic
Genetic Polymorphism
Single Nucleotide Polymorphism
Genotype Determination

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