title: Expression QTL modules as functional components underlying higher-order phenotypes.
abstract: Systems genetics studies often involve the mapping of numerous regulatory relations between genetic loci and expression traits. These regulatory relations form a bipartite network consisting of genetic loci and expression phenotypes. Modular network organizations may arise from the pleiotropic and polygenic regulation of gene expression. Here we analyzed the expression QTL (eQTL) networks derived from expression genetic data of yeast and mouse liver and found 65 and 98 modules respectively. Computer simulation result showed that such modules rarely occurred in randomized networks with the same number of nodes and edges and same degree distribution. We also found significant within-module functional coherence. The analysis of genetic overlaps and the evidences from biomedical literature have linked some eQTL modules to physiological phenotypes. Functional coherence within the eQTL modules and genetic overlaps between the modules and physiological phenotypes suggests that eQTL modules may act as functional units underlying the higher-order phenotypes.
authors.affiliation: Department of Molecular Sciences, University of Tennessee Health Science Center, Memphis, Tennessee, United States of America. lebao@ucsd.edu
authors.forename: Lei
authors.initials: L
authors.lastname: Bao
authors.forename: Xuefeng
authors.initials: X
authors.lastname: Xia
authors.forename: Yan
authors.initials: Y
authors.lastname: Cui
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D016208:Databases, Factual; D004843:Epistasis, Genetic; D005189:False Positive Reactions; D005786:Gene Expression Regulation; D005800:Genes, Fungal; D008099:Liver / Q000378:metabolism; D051379:Mice; D008957:Models, Genetic; D010641:Phenotype; D040641:Quantitative Trait Loci; D012984:Software