Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS
Abstract
The goal of this grant proposal was to: 1) construct a prostate tissue-specific expression quantitative trait loci (eQTL) dataset; and 2) utilize this dataset to identify candidate genes for existing prostate cancer (PC) risk-single nucleotide polymorphisms (SNPs) that could then be followed up in future studies. To accomplish this goal we performed a genomewide SNP analysis (Illumina Human Omni 2.5M SNP array) and a genome-wide mRNA expression analysis (RNA sequencing) on a common set of 500 samples of normal prostate tissue sampled from men with PC. Of 500 processed samples, 471 samples passed stringent quality control (QC) and were available for further analysis. Our primary analysis focused on identifying eQTLs for 146 PC risk-SNPs, including all SNPs in linkage disequilibrium with each risk-SNP (r2 >0.5), resulting in 100 unique risk-intervals. Furthermore, we focused on cis-acting associations only where the transcript was located within 2Mb (+/-1Mb) of the risk-SNP interval. Of all SNPs located in the 100 risk-intervals (N=6324 SNPs), 1,718 demonstrated a significant eQTL signal after adjustment for sample histology (% lymphocytes and % epithelial cells) and meeting a Bonferroni-adjusted p-value threshold of 1.96 e-7 (ranged from 1.96 e-7 to 1.52 e-91). Of the 100 PC riskintervals, 31 (31%) demonstrated a significant eQTL signal and these were associated with 54 genes.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2014
- Accession Number
- ADA604737
Entities
People
- Stephen Thibodeau
Organizations
- Mayo Clinic