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Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA-seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.

Original publication

DOI

10.1038/ng.3737

Type

Journal article

Journal

Nat Genet

Publication Date

01/2017

Volume

49

Pages

139 - 145

Keywords

Blood Proteins, Cell Lineage, Cohort Studies, Female, Gene Expression Profiling, Genetic Predisposition to Disease, High-Throughput Nucleotide Sequencing, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, RNA, Messenger, Regulatory Sequences, Nucleic Acid