Genetic correlates of gene expression in recombinant inbred strains: a relational model system to explore neurobehavioral phenotypes.

Full genome sequencing, high-density genotyping, expanding sets of microarray assays, and systematic phenotyping of neuroanatomical and behavioral traits are producing a wealth of data on the mouse central nervous system (CNS). These disparate resources are still poorly integrated. One solution is to acquire these data using a common reference population of isogenic lines of mice, providing a point of integration between the data types. Recombinant inbred (RI) mice, derived through inbreeding of progeny from an inbred cross, are a powerful tool for complex trait mapping and analysis of the challenging phenotypes of neuroscientific interest. These isogenic RI lines are a retrievable genetic resource that can be repeatedly studied using a wide variety of assays. Diverse data sets can be related through fixed and known genomes, using tools such as the interactive web-based system for complex trait analysis, www.WebQTL.org. In this report, we demonstrate the use of WebQTL to explore complex interactions among a wide variety of traits--from mRNA transcripts to the impressive behavioral and pharmacological variation among RI strains. The relational approach exploiting a common set of strains facilitates study of multiple effects of single genes (pleiotropy) without a priori hypotheses required. Here we demonstrate the power of this technique through genetic correlation of gene expression with a database of neurobehavioral phenotypes collected in these strains of mice through more than 20 years of experimentation. By repeatedly studying the same panel of mice, early data can be re-examined in light of technological advances unforeseen at the time of their initial collection.