RNA interference (RNAi) is emerging as a powerful tool for mammalian genetic screens. The mission of the Broad RNAi Platform is to realize the enormous potential of RNAi to identify the genes underlying disease processes and to elucidate fundamental biological mechanisms. The RNAi Platform grew out of The RNAi Consortium (TRC), a collaborative effort of six academic research institutions and five leading life sciences organizations. The RNAi Platform and TRC work as an integrated team to develop the materials and technology to enable and enhance RNAi as a tool for mammalian genetic screening. The materials and knowledge generated by this team will be made available to the entire scientific community.
The RNAi Platform is directed by David Root, a physical chemist with significant experience in cell-based screening and building lentiviral-based libraries.
The platform's major activities include:
Platform scientists are creating genome-scale libraries of RNAi reagents, targeting virtually all human and mouse genes, which are carried in lentiviral vectors that allow this library to be introduced into a wide range of cell types. They have also developed a streamlined production process for rapid expansion of the library.
In 2011 the RNAi Platform, in collaboration with the Broad Institute Cancer Program and the Center for Cancer Systems Biology at the Dana-Farber Cancer Institute, made publicly available the human ORFeome library V8.1 providing an additional tool for manipulating the human genome.
Platform scientists are developing and optimizing methods for using the library in high-throughput screening. This has enabled the first arrayed RNAi genetic screens by lentiviral infection as well as pooled screening approaches.
Platform scientists are evaluating the performance of the entire library using quantitative PCR to measure knockdown of the target transcript, to create the first fully-validated lentiviral RNAi libary. They are also testing and optimizing the performance of the library under different conditions, including different cell lines, timepoints, and multiplicity of infection (MOI).
New versions of the library are being developed, as well as new methods to screen large subsets of the existing library.