Exploring regulation in tissues with eQTL networks

Maud Fagny, Joseph N. Paulson, Marieke L. Kuijjer, Abhijeet R. Sonawane, Cho Yi Chen, Camila M. Lopes-Ramos, Kimberly Glass, John Quackenbush*, John Platig

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

Characterizing the collective regulatory impact of genetic variants on complex phenotypes is a major challenge in developing a genotype to phenotype map. Using expression quantitative trait locus (eQTL) analyses, we constructed bipartite networks in which edges represent significant associations between genetic variants and gene expression levels and found that the network structure informs regulatory function. We show, in 13 tissues, that these eQTL networks are organized into dense, highly modular communities grouping genes often involved in coherent biological processes. We find communities representing shared processes across tissues, as well as communities associated with tissue-specific processes that coalesce around variants in tissue-specific active chromatin regions. Node centrality is also highly informative, with the global and community hubs differing in regulatory potential and likelihood of being disease associated.

Original languageEnglish
Pages (from-to)E7841-E7850
JournalProceedings of the National Academy of Sciences of the United States of America
Volume114
Issue number37
DOIs
StatePublished - 12 Sep 2017

Keywords

  • Bipartite networks
  • eQTL
  • Expression quantitative trait locus
  • GTEx
  • GWAS

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