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; J. van Dongen; Jouke 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 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

doi:10.1038/ng.3737

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, J. 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 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

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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 language	English
Pages (from-to)	139-145
Number of pages	7
Journal	Nature Genetics
Volume	49
Issue number	1
Early online date	5 Dec 2016
DOIs	https://doi.org/10.1038/ng.3737
Publication status	Published - Jan 2017

Funding

This work was performed within the framework of the Biobank-Based Integrative Omics Studies (BIOS) consortium funded by BBMRI-NL, a research infrastructure financed by the Dutch government (NWO 184.021.007). This work is supported by a grant from the European Research Council (ERC Starting Grant agreement 637640 ImmRisk) to L.F. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII) and the municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study, and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study are supported by the Netherlands Organization for Scientific Research NWO Investments (175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2) and Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) project 050-060-810. We thank P. Arp, M. Jhamai, M. Verkerk, L. Herrera and M. Peters for their help in creating the GWAS database. Work on cell count estimation was funded by NWO 863.13.011. The LifeLines Deep cohort is made possible by grants from the Top Institute of Food and Nutrition (TiFN GH0001), an ERC advanced grant (FP/2007-2013/ERC grant 2012-322698) and a Spinoza prize (NWO SPI 92-266) to C.W.

Funders	Funder number
BBMRI-NL
Dutch Government
Netherlands Genomics Initiative
RIDE2
Research Institute for Diseases in the Elderly
Top Institute of Food and Nutrition	FP/2007-2013/ERC, 2012-322698, SPI 92-266, TiFN GH0001
European Commission
European Research Council	637640
ZonMw
Erasmus Universiteit Rotterdam
Ministerie van Volksgezondheid, Welzijn en Sport
Erasmus Medisch Centrum
Ministerie van Onderwijs, Cultuur en Wetenschap
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	863.13.011, 014-93-015, 050-060-810, 175.010.2005.011, 911-03-012, 184.021.007

Keywords

Journal Article

Cohort Studies

Netherlands Twin Register (NTR)

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1038/ng.3737

ng.3737_Identification of context-dependent expression quantitative trait loci in whole bloodFinal published version, 1.7 MBLicence: Article 25fa Dutch Copyright Act

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Zhernakova, D. V., Deelen, P., Vermaat, M., van Iterson, M., van Galen, M., Arindrarto, W., van 't Hof, P., Mei, H., van Dijk, F., Westra, H.-J., Bonder, M. J., van Rooij, J., Verkerk, M., Jhamai, P. M., Moed, M., Kielbasa, S. M., Bot, J., Nooren, I., Pool, R., ... Franke, L. (2017). Identification of context-dependent expression quantitative trait loci in whole blood. Nature Genetics, 49(1), 139-145. https://doi.org/10.1038/ng.3737

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Zhernakova, DV, Deelen, P, Vermaat, M, van Iterson, M, van Galen, M, Arindrarto, W, van 't Hof, P, Mei, H, van Dijk, F, Westra, H-J, Bonder, MJ, van Rooij, J, Verkerk, M, Jhamai, PM, Moed, M, Kielbasa, SM, Bot, J, Nooren, I, Pool, R , van Dongen, J , Hottenga, JJ, Stehouwer, CDA, van der Kallen, CJH, Schalkwijk, CG, Zhernakova, A, Li, Y, Tigchelaar, EF, de Klein, N, Beekman, M, Deelen, J, van Heemst, D, van den Berg, LH, Hofman, A, Uitterlinden, AG, Van Greevenbroek, MJ, Veldink, JH, Boomsma, DI, van Duijn, CM, Wijmenga, C, Slagboom, PE, Swertz, MA, Isaacs, A, van Meurs, JBJ, Jansen, R, Heijmans, BT, ’t Hoen, PAC & Franke, L 2017, 'Identification of context-dependent expression quantitative trait loci in whole blood', Nature Genetics, vol. 49, no. 1, pp. 139-145. https://doi.org/10.1038/ng.3737

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AU - Deelen, Patrick

AU - Vermaat, Martijn

AU - van Iterson, Maarten

AU - van Galen, Michiel

AU - Arindrarto, Wibowo

AU - van 't Hof, Peter

AU - Mei, Hailiang

AU - van Dijk, Freerk

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AU - Bonder, Marc Jan

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AU - Jhamai, P Mila

AU - Moed, Matthijs

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AU - van der Kallen, Carla J H

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AU - Zhernakova, Alexandra

AU - Li, Yang

AU - Tigchelaar, Ettje F

AU - de Klein, Niek

AU - Beekman, Marian

AU - Deelen, Joris

AU - van Heemst, Diana

AU - van den Berg, Leonard H

AU - Hofman, Albert

AU - Uitterlinden, André G

AU - Van Greevenbroek, Marleen J.

AU - Veldink, Jan H

AU - Boomsma, Dorret I

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AU - Wijmenga, Cisca

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AU - Swertz, Morris a.

AU - Isaacs, Aaron

AU - van Meurs, Joyce B J

AU - Jansen, Rick

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AB - 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.

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

Abstract

Funding

Keywords

Cohort Studies

UN SDGs

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