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Open Access Highly Accessed Methodology article

A comprehensive platform for highly multiplexed mammalian functional genetic screens

Troy Ketela1, Lawrence E Heisler1, Kevin R Brown1, Ron Ammar12, Dahlia Kasimer1, Anuradha Surendra1, Elke Ericson1, Kim Blakely12, Dina Karamboulas1, Andrew M Smith12, Tanja Durbic1, Anthony Arnoldo1, Kahlin Cheung-Ong1, Judice LY Koh1, Shuba Gopal3, Glenn S Cowley3, Xiaoping Yang3, Jennifer K Grenier3, Guri Giaever124, David E Root3*, Jason Moffat12* and Corey Nislow12*

Author Affiliations

1 Donnelly Centre and Banting & Best Department of Medical Research, University of Toronto, Toronto, Canada

2 Department of Molecular Genetics, University of Toronto, Toronto, Canada

3 Broad Institute, Cambridge, USA

4 Department of Pharmaceutical Sciences, University of Toronto, Toronto, Canada

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BMC Genomics 2011, 12:213  doi:10.1186/1471-2164-12-213

Published: 6 May 2011

Abstract

Background

Genome-wide screening in human and mouse cells using RNA interference and open reading frame over-expression libraries is rapidly becoming a viable experimental approach for many research labs. There are a variety of gene expression modulation libraries commercially available, however, detailed and validated protocols as well as the reagents necessary for deconvolving genome-scale gene screens using these libraries are lacking. As a solution, we designed a comprehensive platform for highly multiplexed functional genetic screens in human, mouse and yeast cells using popular, commercially available gene modulation libraries. The Gene Modulation Array Platform (GMAP) is a single microarray-based detection solution for deconvolution of loss and gain-of-function pooled screens.

Results

Experiments with specially constructed lentiviral-based plasmid pools containing ~78,000 shRNAs demonstrated that the GMAP is capable of deconvolving genome-wide shRNA "dropout" screens. Further experiments with a larger, ~90,000 shRNA pool demonstrate that equivalent results are obtained from plasmid pools and from genomic DNA derived from lentivirus infected cells. Parallel testing of large shRNA pools using GMAP and next-generation sequencing methods revealed that the two methods provide valid and complementary approaches to deconvolution of genome-wide shRNA screens. Additional experiments demonstrated that GMAP is equivalent to similar microarray-based products when used for deconvolution of open reading frame over-expression screens.

Conclusion

Herein, we demonstrate four major applications for the GMAP resource, including deconvolution of pooled RNAi screens in cells with at least 90,000 distinct shRNAs. We also provide detailed methodologies for pooled shRNA screen readout using GMAP and compare next-generation sequencing to GMAP (i.e. microarray) based deconvolution methods.