Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

Abstract

The goals of this grant proposal are 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 can then be followed up in future studies. To accomplish this goal we will perform a genome-wide 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. To date, we have pre-screened normal prostate tissue with the use of H&E stained sections from 4000 men having a radical prostatectomy in order to identify those cases meeting our strict selection criteria for further processing (tissue localized to the posterior region of the prostate, no tumor, no high grade PIN, no BPH, <1% lymphocytes, and the final percent of epithelial cells present >40%). Furthermore, the RNA / DNA purification and DNA genotyping / RNA expression analyses proposed have also been completed. We are now in the final phase of the project. We have completed the quality-control analysis of the genotyping and RNA sequencing results and are now completing the statistical analysis required for the construction of the eQTL dataset.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2013
Accession Number
ADA591115

Entities

People

  • Stephen Thibodeau

Organizations

  • Mayo Clinic

Tags

DTIC Thesaurus Topics

  • Cells
  • Chromosomes
  • Construction
  • Data Sets
  • Diseases And Disorders
  • Information Science
  • Lymphocytes
  • Medical Personnel
  • Neoplasms
  • Probability
  • Prostate Cancer
  • Quality Control
  • Rna Sequence Analysis
  • Sequence Analysis
  • Statistical Analysis
  • Statistics
  • Tissues

Fields of Study

  • Biology

Readers

  • Molecular and genetic basis of cancer.
  • Oncology and Biomarker-Based Cancer Detection.