Integrating Computational Biology and Forward Genetics in Drosophila

Genetic screens are powerful methods for the discovery of gene-phenotype associations. However, a systems biology approach to genetics must leverage the massive amount of omics'' data to enhance the power and speed of functional gene discovery in vivo. Thus far, few computational methods for gene function prediction have been rigorously tested for their performance on a genome-wide scale in vivo. In this work, we demonstrate that integrating genome-wide computational gene prioritization with large-scale genetic screening is a powerful tool for functional gene discovery. To discover genes involved in neural development in Drosophila, we extend our strategy for the prioritization of human candidate disease genes to functional prioritization in Drosophila. We then integrate this prioritization strategy with a large-scale genetic screen for interactors of the proneural transcription factor Atonal using genomic deficiencies and mutant and RNAi collections. Using the prioritized genes validated in our genetic screen, we describe a novel genetic interaction network for Atonal. Lastly, we prioritize the whole Drosophila genome and identify candidate gene associations for ten receptor-signaling pathways. This novel database of prioritized pathway candidates, as well as a web application for functional prioritization in Drosophila, called ENDEAVOUR-HIGHFLY, and the Atonal network, are publicly available resources. A systems genetics approach that combines the power of computational predictions with in vivo genetic screens strongly enhances the process of gene function and gene-gene association discovery.