An Integrated Systems Genetics and Omics Toolkit to Probe Gene Function.

Détails

ID Serval
serval:BIB_BC70095EACF2
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
An Integrated Systems Genetics and Omics Toolkit to Probe Gene Function.
Périodique
Cell systems
Auteur⸱e⸱s
Li H., Wang X., Rukina D., Huang Q., Lin T., Sorrentino V., Zhang H., Bou Sleiman M., Arends D., McDaid A., Luan P., Ziari N., Velázquez-Villegas L.A., Gariani K., Kutalik Z., Schoonjans K., Radcliffe R.A., Prins P., Morgenthaler S., Williams R.W., Auwerx J.
ISSN
2405-4712 (Print)
ISSN-L
2405-4712
Statut éditorial
Publié
Date de publication
24/01/2018
Peer-reviewed
Oui
Volume
6
Numéro
1
Pages
90-102.e4
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
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.

Mots-clé
BXD, PheWAS, QTL, TWAS, ePheWAS, genetic reference population, mediation analysis, systems genetics
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/12/2017 16:13
Dernière modification de la notice
20/08/2019 15:30
Données d'usage