An expanded variant list and assembly annotation identifies multiple novel coding and noncoding genes for prostate cancer risk using a normal prostate tissue eQTL data set

PLoS One. 2019 Apr 8;14(4):e0214588. doi: 10.1371/journal.pone.0214588. eCollection 2019.

Abstract

Prostate cancer (PrCa) is highly heritable; 284 variants have been identified to date that are associated with increased prostate cancer risk, yet few genes contributing to its development are known. Expression quantitative trait loci (eQTL) studies link variants with affected genes, helping to determine how these variants might regulate gene expression and may influence prostate cancer risk. In the current study, we performed eQTL analysis on 471 normal prostate epithelium samples and 249 PrCa-risk variants in 196 risk loci, utilizing RNA sequencing transcriptome data based on ENSEMBL gene definition and genome-wide variant data. We identified a total of 213 genes associated with known PrCa-risk variants, including 141 protein-coding genes, 16 lncRNAs, and 56 other non-coding RNA species with differential expression. Compared to our previous analysis, where RefSeq was used for gene annotation, we identified an additional 130 expressed genes associated with known PrCa-risk variants. We detected an eQTL signal for more than half (n = 102, 52%) of the 196 loci tested; 52 (51%) of which were a Group 1 signal, indicating high linkage disequilibrium (LD) between the peak eQTL variant and the PrCa-risk variant (r2>0.5) and may help explain how risk variants influence the development of prostate cancer.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Genetic Predisposition to Disease*
  • Genetic Variation
  • Genome-Wide Association Study
  • Genotype
  • Humans
  • Linkage Disequilibrium*
  • Male
  • Polymorphism, Single Nucleotide
  • Prostate / pathology
  • Prostatic Neoplasms / diagnosis*
  • Prostatic Neoplasms / genetics
  • Quality Control
  • Quantitative Trait Loci*
  • Risk Factors
  • Sequence Analysis, RNA
  • Transcriptome