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Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Oncode Institute, Amsterdam, the Netherlands; Structural & Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
Luleå University of Technology, Department of Health Sciences, Medical Science. Genetics of Complex Traits, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, United Kingdom; School of Life Sciences, College of Liberal Arts and Science, University of Westminster, London, United Kingdom.ORCID iD: 0000-0001-9672-9477
Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Oncode Institute, Amsterdam, the Netherlands.
Number of Authors: 1102021 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 53, no 9, p. 1300-1310Article in journal (Refereed) Published
Abstract [en]

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

Place, publisher, year, edition, pages
Springer Nature, 2021. Vol. 53, no 9, p. 1300-1310
National Category
Medical Genetics and Genomics
Research subject
Medical Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-86989DOI: 10.1038/s41588-021-00913-zISI: 000692073000001PubMedID: 34475573Scopus ID: 2-s2.0-85115732255OAI: oai:DiVA.org:ltu-86989DiVA, id: diva2:1591365
Note

Godkänd;2021;Nivå 0;2021-09-30 (alebob);

Funder: For funding information, see Acknowledgements https://www.nature.com/articles/s41588-021-00913-z#Ack1

Available from: 2021-09-06 Created: 2021-09-06 Last updated: 2025-10-21Bibliographically approved

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Yaghootkar, Hanieh

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