An eQTL analysis of the human glioblastoma multiforme genome

•This study examines the covariance between genotype at SNP loci and gene expression phenotype in glioblastoma genomes.•Phenotype is defined as the difference between the expression level in tumors vs. normal brain tissue.•The study identified 9257 significant eQTLs associations in the GBM genome.•Genotypes of eQTLs linked to the RNASE3 and BNC2 genes covary with expression levels at hundreds of loci.

In this paper we use eQTL mapping to identify associations between gene dysregulation and single nucleotide polymorphism (SNP) genotypes in glioblastoma multiforme (GBM). A set of 532,954 SNPs was evaluated as predictors of the expression levels of 22,279 expression probes. We identified SNPs associated with fold change in expression level rather than raw expression levels in the tumor. Following adjustment for false discovery rate, the complete set of probes yielded 9257 significant associations (p < 0.05). We found 18 eQTLs that were missense mutations. Many of the eQTLs in the non-coding regions of a gene, or linked to nearby genes, had large numbers of significant associations (e.g. 321 for RNASE3, 101 for BNC2). Functional enrichment analysis revealed that the expression probes in significant associations were involved in signal transduction, transcription regulation, membrane function, and cell cycle regulation. These results suggest several loci that may serve as hubs in gene regulatory pathways associated with GBM.