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

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.

Fig 1. Study Design.

(A) Flow diagram of stages of analyses. In the variant-based analysis, PrCa-risk variant(s) (green bar) and all nearby variants in LD were tested for eQTL signals against all genes +/- 1.1 Mb (red lines) to identify target genes (blue line). In the gene-based analysis, all variants (blue bars) +/- 1.1 Mb from an identified gene (blue line) were evaluated for eQTL associations. (B) Numbers of variants and genes identified during analyses. A total of 10,111 variants (249 PrCa-risk and 9,613 LD variants) in 196 risk loci were tested in the first stage of analysis. Significant eQTL signals were found in 213 genes in 102 loci. Significant genes were identified as protein coding, lncRNA, or other RNA and then grouped according to the LD between the peak eQTL variant and the PrCa-risk variant. Numbers in the Groups indicate the total number of unique genes identified (number of unique novel genes identified. i.e., not previously reported in Thibodeau et al. 2016). Several genes fell into multiple groups due to the gene’s proximity to multiple risk loci. In this figure, each gene is counted only once and is included in the group with the highest LD with the PrCa-risk SNP. For a full list of all genes, please see S2 Table.

Fig 2. TAX1BP1, HOXA13, HOTTIP, and SKIL risk loci.

Risk loci are shown for (A) TAX1BP1, (B) HOXA13, (C) HOTTIP, and (D) SKIL. The x axis shows the chromosomal position of the variants (with analyzed gene in the region below) and the y axis is the -log10 (P-value) obtained by regressing normalized expression levels for the gene listed in the panel title on the number of minor alleles of each variant genotype adjusted for histologic characteristics and 14 expression principal components. PrCa-risk variant is indicated by the dashed red vertical line and the eQTL variant with a diamond. All significant variants are colored, with variants in high LD with the PrCa-risk variant in red (LD>0.5); those with LD between 0.2–0.5 in green, and those with LD≤0.2 in blue. The right y axis shows the recombination rate (purple dashed lines mark recombination locations). The bottom half of each panel contains an LD heat mat of the significant variants in the region.