E-RNAi: a web application to design optimized RNAi constructs

RNA interference (RNAi) has become a powerful genetic approach to systematically dissect gene function on a genome-wide scale. Owing to the penetrance and efficiency of RNAi in invertebrates, model organisms such as Drosophila melanogaster and Caenorhabditis elegans have contributed significantly to the identification of novel components of diverse biological pathways, ranging from early development to fat storage and aging. For the correct assessment of phenotypes, a key issue remains the stringent quality control of long double-stranded RNAs (dsRNA) to calculate potential off-target effects that may obscure the phenotypic data. We here describe a web-based tool to evaluate and design optimized dsRNA constructs. Moreover, the application also gives access to published predesigned dsRNAs. The E-RNAi web application is available at

GenomeRNAi: a database for cell-based RNAi phenotypes

RNA interference (RNAi) has emerged as a powerful tool to generate loss-of-function phenotypes in a variety of organisms. Combined with the sequence information of almost completely annotated genomes, RNAi technologies have opened new avenues to conduct systematic genetic screens for every annotated gene in the genome. As increasing large datasets of RNAi-induced phenotypes become available, an important challenge remains the systematic integration and annotation of functional information. Genome-wide RNAi screens have been performed both in Caenorhabditis elegans and Drosophila for a variety of phenotypes and several RNAi libraries have become available to assess phenotypes for almost every gene in the genome. These screens were performed using different types of assays from visible phenotypes to focused transcriptional readouts and provide a rich data source for functional annotation across different species. The GenomeRNAi database provides access to published RNAi phenotypes obtained from cell-based screens and maps them to their genomic locus, including possible non-specific regions. The database also gives access to sequence information of RNAi probes used in various screens. It can be searched by phenotype, by gene, by RNAi probe or by sequence and is accessible a

GenomeRNAi: a database for cell-based RNAi phenotypes. 2009 update

The GenomeRNAi database (http://www.genomernai.org/) contains phenotypes from published cell-based RNA interference (RNAi) screens in Drosophila and Homo sapiens. The database connects observed phenotypes with annotations of targeted genes and information about the RNAi reagent used for the perturbation experiment. The availability of phenotypes from Drosophila and human screens also allows for phenotype searches across species. Besides reporting quantitative data from genome-scale screens, the new release of GenomeRNAi also enables reporting of data from microscopy experiments and curated phenotypes from published screens. In addition, the database provides an updated resource of RNAi reagents and their predicted quality that are available for the Drosophila and the human genome. The new version also facilitates the integration with other genomic data sets and contains expression profiling (RNA-Seq) data for several cell lines commonly used in RNAi experiments

A combined ex vivo and in vivo RNAi screen for notch regulators in Drosophila reveals an extensive notch interaction network

Notch signaling plays a fundamental role in cellular differentiation and has been linked to human diseases, including cancer. We report the use of comprehensive RNAi analyses to dissect Notch regulation and its connections to cellular pathways. A cell-based RNAi screen identified 900 candidate Notch regulators on a genome-wide scale. The subsequent use of a library of transgenic Drosophila expressing RNAi constructs enabled large-scale in vivo validation and confirmed 333 of 501 tested genes as Notch regulators. Mapping the phenotypic attributes of our data on an interaction network identified another 68 relevant genes and revealed several modules of unexpected Notch regulatory activity. In particular, we note an intriguing relationship to pyruvate metabolism, which may be relevant to cancer. Our study reveals a hitherto unappreciated diversity of tissue-specific modulators impinging on Notch and opens new avenues for studying Notch regulation and function in development and disease