74
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          RNA interference (RNAi) screening is a state-of-the-art technology that enables the dissection of biological processes and disease-related phenotypes. The commercial availability of genome-wide, short hairpin RNA (shRNA) libraries has fueled interest in this area but the generation and analysis of these complex data remain a challenge. Here, we describe complete experimental protocols and novel open source computational methodologies, shALIGN and shRNAseq, that allow RNAi screens to be rapidly deconvoluted using next generation sequencing. Our computational pipeline offers efficient screen analysis and the flexibility and scalability to quickly incorporate future developments in shRNA library technology.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: not found

          A large genome center's improvements to the Illumina sequencing system.

          The Wellcome Trust Sanger Institute is one of the world's largest genome centers, and a substantial amount of our sequencing is performed with 'next-generation' massively parallel sequencing technologies: in June 2008 the quantity of purity-filtered sequence data generated by our Genome Analyzer (Illumina) platforms reached 1 terabase, and our average weekly Illumina production output is currently 64 gigabases. Here we describe a set of improvements we have made to the standard Illumina protocols to make the library preparation more reliable in a high-throughput environment, to reduce bias, tighten insert size distribution and reliably obtain high yields of data.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Highly parallel identification of essential genes in cancer cells.

            More complete knowledge of the molecular mechanisms underlying cancer will improve prevention, diagnosis and treatment. Efforts such as The Cancer Genome Atlas are systematically characterizing the structural basis of cancer, by identifying the genomic mutations associated with each cancer type. A powerful complementary approach is to systematically characterize the functional basis of cancer, by identifying the genes essential for growth and related phenotypes in different cancer cells. Such information would be particularly valuable for identifying potential drug targets. Here, we report the development of an efficient, robust approach to perform genome-scale pooled shRNA screens for both positive and negative selection and its application to systematically identify cell essential genes in 12 cancer cell lines. By integrating these functional data with comprehensive genetic analyses of primary human tumors, we identified known and putative oncogenes such as EGFR, KRAS, MYC, BCR-ABL, MYB, CRKL, and CDK4 that are essential for cancer cell proliferation and also altered in human cancers. We further used this approach to identify genes involved in the response of cancer cells to tumoricidal agents and found 4 genes required for the response of CML cells to imatinib treatment: PTPN1, NF1, SMARCB1, and SMARCE1, and 5 regulators of the response to FAS activation, FAS, FADD, CASP8, ARID1A and CBX1. Broad application of this highly parallel genetic screening strategy will not only facilitate the rapid identification of genes that drive the malignant state and its response to therapeutics but will also enable the discovery of genes that participate in any biological process.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Second-generation shRNA libraries covering the mouse and human genomes.

              Loss-of-function phenotypes often hold the key to understanding the connections and biological functions of biochemical pathways. We and others previously constructed libraries of short hairpin RNAs that allow systematic analysis of RNA interference-induced phenotypes in mammalian cells. Here we report the construction and validation of second-generation short hairpin RNA expression libraries designed using an increased knowledge of RNA interference biochemistry. These constructs include silencing triggers designed to mimic a natural microRNA primary transcript, and each target sequence was selected on the basis of thermodynamic criteria for optimal small RNA performance. Biochemical and phenotypic assays indicate that the new libraries are substantially improved over first-generation reagents. We generated large-scale-arrayed, sequence-verified libraries comprising more than 140,000 second-generation short hairpin RNA expression plasmids, covering a substantial fraction of all predicted genes in the human and mouse genomes. These libraries are available to the scientific community.
                Bookmark

                Author and article information

                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2011
                21 October 2011
                : 12
                : 10
                : R104
                Affiliations
                [1 ]The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK
                Article
                gb-2011-12-10-r104
                10.1186/gb-2011-12-10-r104
                3333774
                22018332
                aa1981ae-d318-4b6b-a3a9-b725a890d85c
                Copyright ©2011 Sims et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 June 2011
                : 25 September 2011
                : 21 October 2011
                Categories
                Method

                Genetics
                Genetics

                Comments

                Comment on this article