Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

, Urmo Võsa (Lead / Corresponding author), Annique Claringbould (Lead / Corresponding author), Harm-Jan Westra, Marc Jan Bonder, Patrick Deelen, Biao Zeng, Holger Kirsten, Ashis Saha, Roman Kreuzhuber, Seyhan Yazar, Harm Brugge, Roy Oelen, Dylan H de Vries, Monique G P van der Wijst, Silva Kasela, Natalia Pervjakova, Isabel Alves, Marie-Julie Favé, Mawussé AgbessiMark W Christiansen, Rick Jansen, Ilkka Seppälä, Lin Tong, Alexander Teumer, Katharina Schramm, Gibran Hemani, Joost Verlouw, Hanieh Yaghootkar, Reyhan Sönmez Flitman, Andrew Brown, Viktorija Kukushkina, Anette Kalnapenkis, Sina Rüeger, Eleonora Porcu, Jaanika Kronberg, Johannes Kettunen, Bernett Lee, Futao Zhang, Ting Qi, Jose Alquicira Hernandez, Wibowo Arindrarto, Frank Beutner, Julia Dmitrieva, Mahmoud Elansary, Benjamin P. Fairfax, Michel Georges, Bastiaan T Heijmans, Alex W Hewitt, Mika Kähönen, Yungil Kim

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)1300-1310
Number of pages22
JournalNature Genetics
Volume53
Early online date2 Sep 2021
DOIs
Publication statusPublished - Sep 2021

Keywords

  • Gene expression
  • Gene regulation
  • Genome-wide association studies

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