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 Velazquez-Villegas, Karim Gariani, Zoltán Kutalik, Kristina Schoonjans, Richard A Radcliffe, Pjotr Prins, Stephan Morgenthaler, Robert W WilliamsJohan Auwerx*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)
7 Downloads (Pure)


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 ( 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.
Original languageEnglish
Pages (from-to)90-102.e4
Number of pages18
JournalCell Systems
Issue number1
Early online date30 Nov 2017
Publication statusPublished - 24 Jan 2018
Externally publishedYes


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