Genetic interactions influence many phenotypes and can be used as a powerful experimental tool to discover functional relationships between genes. Here we describe a robust and scalable method to systematically map genetic interactions in human cancer cells using combinatorial RNAi and high-throughput imaging. Through automated, single-cell phenotyping, we measured genetic interactions across a broad spectrum of phenotypes, including cell count, cell eccentricity and nuclear area. We mapped genetic interactions of epigenetic regulators in colon cancer cells, recovering known protein complexes. Our study also revealed the prospects and challenges of studying genetic interactions in human cells using multiparametric phenotyping.
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We thank T. Horn, T. Sandmann and members of the Boutros and Huber groups for helpful discussions. M. Boutros is supported by a European Research Council Advanced Grant (“Syngene”). W.H. acknowledges support by the European Union project Systems Microscopy. C.L. and B.F. were supported by the CellNetworks Cluster of Excellence of the German Research Foundation (DFG).
The authors declare no competing financial interests.
Supplementary Figures 1–6 (PDF 1325 kb)
Target genes (XLS 56 kb)
siRNA designs (XLS 149 kb)
qPCR primers (XLS 75 kb)
Screened siRNAs (XLS 68 kb)
Interaction scores (XLS 10537 kb)
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Laufer, C., Fischer, B., Billmann, M. et al. Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. Nat Methods 10, 427–431 (2013) doi:10.1038/nmeth.2436
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