Identification of context-dependent expression quantitative trait loci in whole blood

Daria V Zhernakova, Patrick Deelen, Martijn Vermaat, Maarten van Iterson, Michiel van Galen, Wibowo Arindrarto, Peter van 't Hof, Hailiang Mei, Freerk van Dijk, Harm-Jan Westra, Marc Jan Bonder, Jeroen van Rooij, Marijn Verkerk, P Mila Jhamai, Matthijs Moed, Szymon M Kielbasa, Jan Bot, Irene Nooren, René Pool, Jenny van DongenJouke J Hottenga, Coen D A Stehouwer, Carla J H van der Kallen, Casper G Schalkwijk, Alexandra Zhernakova, Yang Li, Ettje F Tigchelaar, Niek de Klein, Marian Beekman, Joris Deelen, Diana van Heemst, Leonard H van den Berg, Albert Hofman, André G Uitterlinden, Marleen M J van Greevenbroek, Jan H Veldink, Dorret I Boomsma, Cornelia M van Duijn, Cisca Wijmenga, P Eline Slagboom, Morris A Swertz, Aaron Isaacs, Joyce B J van Meurs, Rick Jansen, Bastiaan T Heijmans, Peter A C 't Hoen, Lude Franke

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

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 languageEnglish
Pages (from-to)139–145
Number of pages7
JournalNature Genetics
Volume49
Issue number1
DOIs
Publication statusPublished - Jan 2017

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