Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

Exposure expression quantitative trait loci (e2QTL)

The analysis of e2QTL allows for the identification of context-specific eQTL effects (Kim-Hellmuth et al. (2017), PMID: 28814792). To evaluate how inter-individual genetic variability influences the regulation of DNA damage-induced apoptosis, we performed e2QTL analysis of CD8+ T cells from 461 healthy European participants stimulated with high doses of 5 different carcinogens. These include Methyl-methanesulfonate (MMS), tert-butyl-hydroperoxide (TBOOH), benzo(a)pyrene-7,8-diol-9,10-epoxide (BPDE), 4-hydroxycyclophosphamide (HC) and UVC radiation.

eQTL_DNA_damage_induced_apoptosis.csv: eQTL data. FastQTL was used to analyze cis-eQTL within a 1 MB window of a gene’s transcription start site. Filtering and normalization of expression data was performed as described by the Genotype Tissue Expression (GTEx) project (The GTEx Consortium (2015), PMID: 25954001) including 60 PEER factors, top 3 genotype PCs and sex as covariates. Genotypes were filtered by PHWE > 10-6 and MAF > 5 %. Adjusted p-values were generated using 1,000 to 10,000 permutations. Variant IDs (CHR:POS:REF:ALT) are based on GRCh38.

e2QTL_DNA_damage_induced_apoptosis.csv: e2QTL data. The most significant variant for each analyzed gene was determined based on eQTL data to calculate e2QTL in a z-test that were corrected for multiple testing using Bonferroni correction as described by Kim-Hellmuth et al. (2017). Variant IDs (CHR:POS:REF:ALT) are based on GRCh38.