title: A block mixture model to map eQTLs for gene clustering and networking.
abstract: To study how genes function in a cellular and physiological process, a general procedure is to classify gene expression profiles into categories based on their similarity and reconstruct a regulatory network for functional elements. However, this procedure has not been implemented with the genetic mechanisms that underlie the organization of gene clusters and networks, despite much effort made to map expression quantitative trait loci (eQTLs) that affect the expression of individual genes. Here we address this issue by developing a computational approach that integrates gene clustering and network reconstruction with genetic mapping into a unifying framework. The approach can not only identify specific eQTLs that control how genes are clustered and organized toward biological functions, but also enable the investigation of the biological mechanisms that individual eQTLs perturb in a signaling pathway. We applied the new approach to characterize the effects of eQTLs on the structure and organization of gene clusters in Caenorhabditis elegans. This study provides the first characterization, to our knowledge, of the effects of genetic variants on the regulatory network of gene expression. The approach developed can also facilitate the genetic dissection of other dynamic processes, including development, physiology and disease progression in any organisms.
authors.affiliation: Department of Biostatistics, University of Texas School of Public Health, Houston, TX 77030, USA.|Department of Public Health Sciences, The Pennsylvania State University, Hershey, PA 17033, USA.
authors.forename: Ningtao
authors.initials: N
authors.lastname: Wang
authors.affiliation: Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA.
authors.forename: Kirk
authors.initials: K
authors.lastname: Gosik
authors.affiliation: Department of Biostatistics, University of Texas School of Public Health, Houston, TX 77030, USA.|Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA.
authors.forename: Runze
authors.initials: R
authors.lastname: Li
authors.affiliation: Department of Biostatistics, University of Texas School of Public Health, Houston, TX 77030, USA.
authors.forename: Bruce
authors.initials: B
authors.lastname: Lindsay
authors.affiliation: Department of Biostatistics, University of Texas School of Public Health, Houston, TX 77030, USA.|Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA.
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D000818:Animals; D017173:Caenorhabditis elegans / Q000235:genetics; D002874:Chromosome Mapping; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D053263:Gene Regulatory Networks; D055106:Genome-Wide Association Study; D005838:Genotype; D005810:Multigene Family; D040641:Quantitative Trait Loci; D012372:ROC Curve; D015203:Reproducibility of Results