Journal
PLOS GENETICS
Volume 2, Issue 8, Pages 1182-1192Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.0020130
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Funding
- NHGRI NIH HHS [T32 HG002536] Funding Source: Medline
- NHLBI NIH HHS [P01 HL030568, P01 HL028481, HL28481, HL30568] Funding Source: Medline
- NIAID NIH HHS [U19 AI063603, 1U19AI063603-01] Funding Source: Medline
- NIGMS NIH HHS [GM08234, T32 GM007104, GM07104] Funding Source: Medline
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Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight-related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.
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