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Integrated Platform for Genome-Wide Screening and Construction of High Integrated platform for genome-wide screening and PNAS PLUS construction of high-density genetic interaction maps in mammalian cells Martin Kampmanna,b, Michael C. Bassika,b, and Jonathan S. Weissmana,b,1 aDepartment of Cellular and Molecular Pharmacology, California Institute for Quantitative Biomedical Research and bHoward Hughes Medical Institute, University of California, San Francisco, CA 94158 Contributed by Jonathan S. Weissman, April 25, 2013 (sent for review February 23, 2013) A major challenge of the postgenomic era is to understand how function of another gene. In GI maps, GIs are determined for human genes function together in normal and disease states. In a large number of pairwise combinations of genes, and genes are microorganisms, high-density genetic interaction (GI) maps are clustered based on the similarity of their GI patterns. The clus- a powerful tool to elucidate gene functions and pathways. We tering typically reveals groups of genes that encode physically have developed an integrated methodology based on pooled interacting proteins or act in a common pathway (17). shRNA screening in mammalian cells for genome-wide identifica- In human cells, such a systematic elucidation of the functional tion of genes with relevant phenotypes and systematic mapping of interactions between human genes will be key to understanding all GIs among them. We recently demonstrated the potential of this how combinations of genes cause common polygenetic diseases approach in an application to pathways controlling the suscepti- and to developing precise therapies based on a patient’s genetic bility of human cells to the toxin ricin. Here we present the background. Additionally, GI maps can detect rare synthetic complete quantitative framework underlying our strategy, includ- lethal gene pairs, which would be ideal drug targets for combi- ing experimental design, derivation of quantitative phenotypes nation therapies that prevent the development of drug resistance from pooled screens, robust identification of hit genes using ultra- of rapidly evolving diseases like cancer. complex shRNA libraries, parallel measurement of tens of thou- We recently established a technology platform for constructing sands of GIs from a single double-shRNA experiment, and con- high-density GI maps in mammalian cells based on pooled struction of GI maps. We describe the general applicability of our shRNA screens and demonstrated its potential by using it to strategy. Our pooled approach enables rapid screening of the same identify pathways controlling the sensitivity of human cells to the shRNA library in different cell lines and under different conditions toxin ricin (18). Our two-step strategy integrates several key to determine a range of different phenotypes. We illustrate this innovations to address the challenges to the effective application strategy here for single- and double-shRNA libraries. We compare of RNAi-based approaches to study gene function in mammalian the roles of genes for susceptibility to ricin and Shiga toxin in systems. A primary genome-wide screen is conducted using an different human cell lines and reveal both toxin-specific and cell ultra-complex shRNA library to identify genes of interest. A line-specific pathways. We also present GI maps based on growth double-shRNA library targeting all pairwise combinations of hit and ricin-resistance phenotypes, and we demonstrate how such genes from the primary screen then is used to measure genetic a comparative GI mapping strategy enables functional dissection of interactions based on a pooled experiment. physical complexes and context-dependent pathways. Here, we describe a principled framework for collecting and analyzing data and illustrate the broad potential of our approach. epistasis | RNA interference | synthetic lethality | functional genomics | We extract different quantitative, shRNA-intrinsic phenotypes, human genome such as growth or drug sensitivity, from pooled screens. We es- tablish a strategy for robust identification of hit genes in pri- he first human genome sequence was determined more than mary screens. Individual shRNAs targeting these hit genes are T10 years ago (1, 2), and the revolution in sequencing tech- nology has facilitated the deciphering of hundreds more human Significance and cancer genomes since then (3, 4). The next frontier is the development of strategies for the systematic elucidation of gene While genomes are being sequenced at an accelerating pace, function in health and disease contexts. the elucidation of the function of human genes and their inter- RNAi technology has facilitated genetic approaches in mam- actions remains a formidable challenge. Genetic interaction malian cells, but the analysis of genome-wide RNAi screens maps, which report on how genes work together, provide a remains challenging (5). Major confounding factors are false- fi fi powerful tool for systematically de ning gene function and negative results caused by insuf ciently active shRNAs and false- pathways. Here we present the complete quantitative frame- positive results caused by off-target effects. Indeed, the challenges work underlying our recently developed approach for systematic of off-target effects have been highlighted recently in papers mapping of genetic interactions in mammalian cells and dem- by Schultz et al (6) and Adamson et al. (7), which show that onstrate its broad potential. Maps obtained in different cell these effects can be pervasive in genome-wide screens and are types and treatment conditions dissect context-dependent not robustly detected by some of the standard precautions pathways. Our approach can provide a rational basis for de- typically used. fining combination therapies by targeting genes with strong fi Furthermore, even when hit genes are identi ed correctly, genetic interactions. effective follow-up to uncover their function often requires intense effort. In yeast and other microorganisms, high-density Author contributions: M.K., M.C.B., and J.S.W. designed research, performed research, genetic interaction (GI) maps have been highly successful at contributed new reagents/analytic tools, analyzed data, and wrote the paper. defining gene function, revealing functional relationships be- The authors declare no conflict of interest. tween previously uncharacterized genes and elucidating cellular 1To whom correspondence should be addressed. E-mail: [email protected]. – pathways (8 16). GIs quantify the effect that the loss of func- This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. SYSTEMS BIOLOGY tion of one gene has on the phenotype caused by the loss of 1073/pnas.1307002110/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1307002110 PNAS | Published online June 5, 2013 | E2317–E2326 Downloaded by guest on September 25, 2021 selected to construct focused single-shRNA and double-shRNA strategy facilitates the dissection of functional pathways in libraries. We demonstrate the use of focused libraries to compare different conditions and cellular states. pathways controlling sensitivity of different human cell lines to Results ricin and Shiga toxin. We describe our strategy for constructing a high-density GI map based on pooled screening of a double- Integrated Platform for Genome-Wide Screening and Mapping of shRNA library. We show how shRNAs with partial off-target Genetic Interactions. We have developed an integrated suite of experimental and computational approaches to identify genes of effects can be identified and removed from GI maps. GI maps can interest robustly using pooled shRNA-based screens in mam- be constructed based on different quantitative phenotypes. As malian cells and to map genetic interactions between these genes described in Discussion, our strategy has several features that systematically to uncover functional relationships. This section and distinguish it from array-based approaches in which individual Fig. 1 give an overview of our multistep strategy; the subsequent combinations of genes are targeted by interfering RNAs in sep- sections provide the rationale, describe the details, and demonstrate – arate wells (19 21). Importantly, the same double-shRNA library the performance of the individual steps. can be screened rapidly for different phenotypes to compare First, we conduct a primary genome-wide screen (Fig. 1A)using context-specific GI maps. We compare a growth-based GI map an ultra-complex shRNA library. Our current shRNA library tar- and a ricin resistance-based GI map to illustrate how this gets each human protein-coding gene with ∼25 independent A PRIMARY SCREEN High-density oligonucleotide array synthesis Selection based on growth or shRNAs targeting gene A Negative control shRNAs Genome wide shRNA library: physical separation • Ultracomplex (~25 different shRNAs / gene) • Large number of negative control (NC) shRNAs Selected A NC Mammalian Infected cells, B A A cells NC before selection NC Determine B Selected A A NC Split frequencies B B by deep Unselected Lentiviral A NC A sequencing A NC infection B B NC • P values for hit genes Unselected • Active shRNAs for hit genes B HIT shRNA LIBRARY • Screen in different cell lines Experiments Focused library of active shRNAs • Screen with different selection agents Phenotype and negative control (NC) shRNAs Pooled digest, ligation to create all Genes C DOUBLE-shRNA SCREEN pairwise double shRNAs Double-shRNA library High-density quantitative GI map First shRNA Active NC First Gene Phenotypes for Calculate Filter shRNAs Cluster
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