International Mammalian Genome Society

The 16th International Mouse Genome Conference (2002)

Plenary Presentations * Oral Presentations *
Poster Presentations: Complex Genetics and Disease Modifiers * Developmental Genetics * Functional Genomics * Gene Discovery * Genetic Manipulations to Alter Gene Function * Mouse Models: Human Disease and Pharmacogenetics * Sequence Annotation and Comparative Analysis of Genomes *
Attendees * Sponsors * Table of Contents * Photographs * Awards

Oral Presentation

Wednesday 20 November

10:15 – 10:30 HRS

ELUCIDATING GENE REGULATORY NETWORKS INVOLVED IN HAIR AND SKIN PHYSIOLOGY BY INTEGRATING EXPERIMENTAL AND COMPUTATIONAL APPROACHES

B. Jones
ORNL

Co-Authors: Leuze M, Snoddy J, Schmoyer D, Baker E, Das S, Hoyt P,  Doktycz M, Culiat C, Michaud E
Institutions: Oak Ridge National Laboratory

The ongoing availability of complete genomic sequence from human, mouse, and multiple other organisms creates unprecedented opportunities to study gene regulatory networks (GRNs).  We are combining genome-scale experimental and computational approaches to develop an integrated method of identifying GRNs that are important in mouse hair and skin physiology. Experimentally, we use cDNA microarrays to identify large sets of co-regulated genes.  Our initial efforts focus on a novel Oak Ridge mutation (Hrn) in a transcription factor encoded by the hairless (hr) gene. Hairless mutants are characterized by early and persistent loss of body hair, and by increased susceptibility to UV- and chemical-induced carcinogenesis and dioxin toxicity. We have identified numerous genes that are differentially expressed in the skin of Hrn mutants, thus elucidating some of the components of the regulatory network associated with the hairless transcription factor. The parallel computational approach consists of two components: 1.) identifying orthologs (mouse, human, other species available) for each gene identified as interesting by microarray analyses and then applying phylogenetic footprinting to distinguish evolutionarily-conserved regions of noncoding DNA for each set of orthologs, and 2.) developing a novel algorithm to identify transcription factor binding motifs within footprinted regions of DNA.  We also incorporate known biological information, such as Gene OntologyTM classification, to enhance our assignment of genes into individual networks.  In the future our effort will be extended to a more comprehensive analysis of additional skin and hair mutants. Ultimately this approach will be applicable to any biology of interest.