Exploring regulation in tissues with eQTL networks

Citation:

Maud Fagny, Joseph N Paulson, Marieke L Kuijjer, Abhijeet R Sonawane, Cho-Yi Chen, Camila M Lopes-Ramos, Kimberly Glass, John Quackenbush, and John Platig. 2017. “Exploring regulation in tissues with eQTL networks.” Proc Natl Acad Sci U S A, 114, 37, Pp. E7841–E7850. Publisher's Version

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.
Last updated on 09/25/2017