Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors.

Jennifer L Caswell,Noah Zaitlen,Steven E Brenner,Andrei Goga,Roman Camarda,Scott Huntsman,Alicia Y Zhou,Elad Ziv,Donglei Hu

doi:10.1093/hmg/ddv432

Abstract

Genome-wide association studies have identified over 70 single-nucleotide polymorphisms (SNPs) associated with breast cancer. A subset of these SNPs are associated with quantitative expression of nearby genes, but the functional effects of the majority remain unknown. We hypothesized that some risk SNPs may regulate alternative splicing. Using RNA-sequencing data from breast tumors and germline genotypes from The Cancer Genome Atlas, we tested the association between each risk SNP genotype and exon-, exon–exon junction- or transcript-specific expression of nearby genes. Six SNPs were associated with differential transcript expression of seven nearby genes at FDR < 0.05 (BABAM1, DCLRE1B/PHTF1, PEX14, RAD51L1, SRGAP2D and STXBP4). We next developed a Bayesian approach to evaluate, for each SNP, the overlap between the signal of association with breast cancer and the signal of association with alternative splicing. At one locus (SRGAP2D), this method eliminated the possibility that the breast cancer risk and the alternate splicing event were due to the same causal SNP. Lastly, at two loci, we identified the likely causal SNP for the alternative splicing event, and at one, functionally validated the effect of that SNP on alternative splicing using a minigene reporter assay. Our results suggest that the regulation of differential transcript isoform expression is the functional mechanism of some breast cancer risk SNPs and that we can use these associations to identify causal SNPs, target genes and the specific transcripts that may mediate breast cancer risk.

Highlights

Genome-wide association studies (GWASs) have identified thousands of disease risk-associated single-nucleotide polymorphisms, including, to date, 75 that are associated with breast cancer risk [1]
For each of the breast cancer risk-associated single-nucleotide polymorphisms (raSNPs), we searched for differential transcript isoform expression of nearby genes (Supplementary Material, Table S1), adjusting for overall gene expression, global expression variability [16,17] and genetic ancestry
When the analysis was repeated in the smaller set of estrogen receptor (ER)-negative tumors, we identified four associations with four raSNPs, including two exon associations, two junction associations and two transcript associations (Supplementary Material, Table S5), all of which were identified in the ER-positive tumors

Summary

Introduction

Genome-wide association studies (GWASs) have identified thousands of disease risk-associated single-nucleotide polymorphisms (raSNPs), including, to date, 75 that are associated with breast cancer risk [1]. The vast majority of raSNPs are located in noncoding regions of the genome; they, or SNPs in linkage disequilibrium (LD) with them, are likely to influence risk by affecting the regulation of nearby genes or noncoding RNAs [2,3] To determine their function, investigators have tested their association with expression levels of nearby genes (expression quantitative trait loci, or eQTLs) in cis [4,5,6,7] or in trans [4] and assessed whether SNPs in LD with the index raSNP demonstrate evidence for transcription factor binding or histone methylation [6,8]. GWAS variants are modestly enriched for splicing QTLs as well as for eQTLs [9], suggesting that some raSNPs may affect risk by affecting differential transcript expression

Methods

Results

Conclusion