Genome-wide identification of directed gene networks using large-scale population genomics data

Rene Luijk, Koen F. Dekkers, Maarten van Iterson, Wibowo Arindrarto, Annique Claringbould, Paul Hop, Dorret Boomsma, Cornelia M. van Duijn, Marleen M. J. van Greevenbroek, Jan H. Veldink, Cisca Wijmenga, Lude Franke, Peter A. C. 't Hoend, Rick Jansen, Joyce van Meurs, Hailiang Mei, P. Eline Slagboomi, Bastiaan T. Heijmans*, Erik W. van Zwet*, BIOS Consortium

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Web of Science)

Abstract

Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. Here, we develop a method for the large-scale inference of gene-gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). Analysis of genotype and whole-blood RNA-sequencing data from 3072 individuals identified 49 genes as drivers of downstream transcriptional changes (Wald P < 7 x 10(-10)), among which transcription factors were over-represented (Fisher's P = 3.3 x 10(-7)). Our analysis suggests new gene functions and targets, including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6600 genes with a genetic instrument can be explored individually using a web-based browser.
Original languageEnglish
Article number3097
Number of pages10
JournalNature Communications
Volume9
DOIs
Publication statusPublished - 6 Aug 2018

Keywords

  • MENDELIAN RANDOMIZATION
  • TRANSCRIPTIONAL REGULATION
  • ENDOGENOUS RETROVIRUSES
  • INSULIN-SECRETION
  • HUMAN TISSUES
  • TRANS-EQTLS
  • SAMPLE-SIZE
  • CELL-DEATH
  • RNA-SEQ
  • ASSOCIATION
  • APOPTOSIS
  • HAIR
  • ZAC1
  • EXPRESSION

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