Algorithm and genome-wide database of functional siRNAs

DESCRIPTION (provided by applicant): Despite the recent completion of the human genome project, an ostensibly more difficult post-genomic challenge will be the functional annotation of all human genes and integration of this information into an operational cell-based model. Unfortunately, this is at present challenging, primarily due to the absence of reliable experimental and bioinformatic toolsets to rapidly delineate and describe gene function en masse. RNA interference (RNAi) has proven to be an extremely potent and versatile experimental tool to specifically reduce expression of targeted genes, allowing for loss-of-function genetic screens in mammalian cells. Despite these successes, high-throughput (HT) RNAi screening is technically challenging and significant limitations in the technology exist. To address these issues, and to expand on previous program funding, we have developed a novel experimental platform to identify functional shRNAs at a genome-wide scale. The ultimate goal of the proposed project is to develop and make available in public domains a genome-wide database of functionally validated (FV) shRNAs with minimum off-target effects and software for prediction of effective shRNAs. Under Phase II, we propose to develop a FV shRNA data set for 20,000 human genes selected from the RefSeq database. In collaboration with our bioinformatics consultants at University of Rochester and University of Utah, we will develop and maintain a FV shRNA database and algorithm for prediction of the most efficient siRNAs. Then, we will extend this program to include the development of databases comprising a genome-wide FV mouse shRNAs without off-target activity. The FV shRNA databases will be used to develop and release as a commercial product FV shRNA libraries cloned into lentiviral vectors. Genetic screens with FV siRNA libraries have the potential to greatly simplify validation of gene function and significantly impact the molecular dissection of human disease mechanisms. These reagents harbor considerable promise to identify new targets for therapeutic intervention, and the development of increasingly relevant paradigms for drug discovery. As a result, we foresee that these toolsets will significantly improve the efficiency, economy, and ease of performing HT RNAi screens, and will provide basic researchers with preferred, cost-effective alternatives to existing commercially available reagents. The ultimate goal of the proposed project is to develop and make commercially available new, powerful research bioinformatics tools: a database of functionally validated, genome-wide human and mouse shRNAs and algorithms for prediction of functional shRNAs. We propose to apply these tools to develop genome-wide functionally validated siRNA libraries designed for high-throughput discovery of novel drug targets. The developed bioinformatics tools and technologies will significantly improve the efficiency of translational research related to molecular dissection of diverse human disease mechanisms, development of new pharmaceuticals, and therefore, have major implications for improving drug discovery research.