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An Integrated Systems Genetics and Omics Toolkit to Probe Gene Function

  • Hao Li
  • , Xu Wang
  • , Daria Rukina
  • , Qingyao Huang
  • , Tao Lin
  • , Vincenzo Sorrentino
  • , Hongbo Zhang
  • , Maroun Bou Sleiman
  • , Danny Arends
  • , Aaron McDaid
  • , Peiling Luan
  • , Naveed Ziari
  • , Laura A. Velázquez-Villegas
  • , Karim Gariani
  • , Zoltan Kutalik
  • , Kristina Schoonjans
  • , Richard A. Radcliffe
  • , Pjotr Prins
  • , Stephan Morgenthaler
  • , Robert W. Williams
  • Johan Auwerx
  • Swiss Federal Institute of Technology Lausanne
  • Humboldt University of Berlin
  • Swiss Institute of Bioinformatics
  • University of Lausanne
  • University of Colorado Anschutz Medical Campus
  • Utrecht University
  • University of Tennessee Health Science Center

Research output: Contribution to journalArticlepeer-review

44 Scopus citations

Abstract

Identifying genetic and environmental factors that impact complex traits and common diseases is a high biomedical priority. Here, we developed, validated, and implemented a series of multi-layered systems approaches, including (expression-based) phenome-wide association, transcriptome-/proteome-wide association, and (reverse-) mediation analysis, in an open-access web server (systems-genetics.org) to expedite the systems dissection of gene function. We applied these approaches to multi-omics datasets from the BXD mouse genetic reference population, and identified and validated associations between genes and clinical and molecular phenotypes, including previously unreported links between Rpl26 and body weight, and Cpt1a and lipid metabolism. Furthermore, through mediation and reverse-mediation analysis we established regulatory relations between genes, such as the co-regulation of BCKDHA and BCKDHB protein levels, and identified targets of transcription factors E2F6, ZFP277, and ZKSCAN1. Our multifaceted toolkit enabled the identification of gene-gene and gene-phenotype links that are robust and that translate well across populations and species, and can be universally applied to any populations with multi-omics datasets. Li et al. here develop and implement a series of systems tools and establish a web resource using multi-omics datasets of the BXD mouse cohort to identify novel associations between genes and phenotypes.

Original languageEnglish
Pages (from-to)90-102.e4
JournalCell Systems
Volume6
Issue number1
DOIs
StatePublished - 24 Jan 2018
Externally publishedYes

Keywords

  • BXD
  • PheWAS
  • QTL
  • TWAS
  • ePheWAS
  • genetic reference population
  • mediation analysis
  • systems genetics

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