Plant & Animal Genomes XVI Conference

January 12-16, 2008
Town & Country Convention Center
San Diego, CA

Systems Genetic Approaches For Finding Complex Disease Genes In Mice And Men

Steve Horvath

  Department of Human Genetics, University of California, Los Angeles, David Geffen School of Medicine 695 Charles E. Young Drive South, Box 708822 Los Angeles, CA 90095-7088

Weighted gene co-expression network analysis (WGCNA) facilitates a systems biologic view of gene expression data. The network framework makes it straightforward to integrate gene expression data with genetic marker data, which facilitates a systems genetic gene screening method.
This talk covers several theoretical topics including network construction, module definition, network based gene screening, and differential network analysis. The methods are illustrated using several applications including human and mouse genetics. For example, we integrate gene expression and genotype data from an F2 mouse intercross to identify physiologically relevant modules. We describe two analysis strategies: single-network analysis and differential network analysis. Single-network analysis reveals the presence of a physiologically interesting module that can be replicated in two distinct mouse crosses. Differential network analysis reveals differences in network connectivity and module structure between two networks based on the liver expression data of lean and obese mice. The results demonstrate the utility of WGCNA in identifying genetic drivers of complex traits and in finding disease pathways. Systems genetic methods may well help chart the path across the gene–trait chasm.
Related articles and material can be found at the following webpage http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/