Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 114, Issue 37, Pages E7841-E7850Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1707375114
Keywords
GTEx; expression quantitative trait locus; eQTL; bipartite networks; GWAS
Categories
Funding
- US National Institutes of Health
- National Heart, Lung, and Blood Institute [5P01HL105339, 5R01HL111759, 5P01HL114501, K25HL133599]
- National Cancer Institute [5P50CA127003, 1R35CA197449, 1U01CA190234, 5P30CA006516]
- National Institute of Allergy and Infectious Disease [5R01AI099204]
- NVIDIA foundation
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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.
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