Genetic dissection of genomewide expression variation in the Drosophila female brain. Elizabeth G. King¹, B. Sanderson², Casey L. McNeil², Anthony D. Long¹, Stuart J. Macdonald². 1) Ecology & Evolutionary Biology, UC Irvine, Irvine, CA; 2) Department of Molecular Biosciences, University of Kansas, 1200 Sunnyside Avenue, Lawrence, Kansas 66045.

   Drosophila melanogaster is widely employed as a model genetic system to understand fundamental aspects of the control of complex trait variation in populations. In addition, the system is increasingly recognized as an important translational model for the study of human neurodegenerative disease and the action of drugs of abuse. As with all complex, polygenic traits identifying the molecular pathways and causative genes responsible for variation in these phenotypes is challenging. Given the community interest in genetically dissecting neurobehavioral traits in flies, we took advantage of a novel resource for genetic analysis to characterize quantitative variation in transcript abundance in Drosophila heads. The Drosophila Synthetic Population Resource (DPSR) is composed of over 1,600 genotyped Recombinant Inbred Lines (RILs) derived from a pair of highly-recombinant synthetic laboratory populations. These two populations were each initially founded by a different set of eight founder strains, ensuring high functional allelic diversity in the DSPR. We generated 600 heterozygous genotypes - the progeny of intercrosses between DSPR lines from the different populations - isolated RNA from mated adult female heads, and subjected each sample to microarray analysis. These data allow us to construct gene networks and capture the full biological complexity of the pathways involved in gene regulation in the Drosophila head and brain. Genomewide expression QTL (eQTL) analysis also provides a high-resolution picture of the location, effect, and population frequency of loci that influence expression variation in the head, and allows us to examine the relative abundance of cis- and trans-regulatory loci. In addition, researchers using the DSPR to genetically dissect neuronal or behavioral phenotypes will be able to exploit our eQTL data for a systems-level analysis of trait variation, and quickly home in on likely candidate genes.