Abstract:
: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.
journal_name
PLoS Genetjournal_title
PLoS geneticsauthors
Ghazalpour A,Doss S,Zhang B,Wang S,Plaisier C,Castellanos R,Brozell A,Schadt EE,Drake TA,Lusis AJ,Horvath Sdoi
10.1371/journal.pgen.0020130subject
Has Abstractpub_date
2006-08-18 00:00:00pages
e130issue
8eissn
1553-7390issn
1553-7404pii
06-PLGE-RA-0128R2journal_volume
2pub_type
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