Letter | Published:

A functional RNAi screen for regulators of receptor tyrosine kinase and ERK signalling

Naturevolume 444pages230234 (2006) | Download Citation



Receptor tyrosine kinase (RTK) signalling through extracellular-signal-regulated kinases (ERKs) has pivotal roles during metazoan development, underlying processes as diverse as fate determination, differentiation, proliferation, survival, migration and growth. Abnormal RTK/ERK signalling has been extensively documented to contribute to developmental disorders and disease, most notably in oncogenic transformation by mutant RTKs1 or downstream pathway components such as Ras and Raf2. Although the core RTK/ERK signalling cassette has been characterized by decades of research using mammalian cell culture and forward genetic screens in model organisms, signal propagation through this pathway is probably regulated by a larger network of moderate, context-specific proteins. The genes encoding these proteins may not have been discovered through traditional screens owing, in particular, to the requirement for visible phenotypes. To obtain a global view of RTK/ERK signalling, we performed an unbiased, RNA interference (RNAi), genome-wide, high-throughput screen in Drosophila cells using a novel, quantitative, cellular assay monitoring ERK activation. Here we show that ERK pathway output integrates a wide array of conserved cellular processes. Further analysis of selected components—in multiple cell types with different RTK ligands and oncogenic stimuli—validates and classifies 331 pathway regulators. The relevance of these genes is highlighted by our isolation of a Ste20-like kinase and a PPM-family phosphatase that seem to regulate RTK/ERK signalling in vivo and in mammalian cells. Novel regulators that modulate specific pathway outputs may be selective targets for drug discovery.

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We thank A. Philippakis and P. Hong for helpful discussions of statistical approaches, M. Melnick for dpERK antibody assistance, L. Kockel for pioneering the phospho-specific antibody high-throughput screen approach in our laboratory and help with in vivo analysis, C. Micchelli and R. Binari for assistance with genetic manipulations and interpretation, and other current and former members of the Perrimon lab for reagents and discussions. We thank L. Kockel, C. Micchelli, M. Kulkarni, B. Neel, R. Dasgupta, R. Binari and B. Mathey-Prevot for critical manuscript review. A.F. is a recipient of the Medical Scientist Training Program (MSTP) grant. N.P. is an investigator of the Howard Hughes Medical Institute.

Author information


  1. Department of Genetics, Howard Hughes Medical Institute, Harvard Medical School, Boston, 77 Avenue Louis Pasteur, Massachusetts, 02115, USA

    • Adam Friedman
    •  & Norbert Perrimon


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Competing interests

Full datasets and dsRNA sequence information are available at the DRSC website (http://www.flyrnai.org). Reprints and permissions information is available at www.nature.com/reprints. The authors declare no competing financial interests.

Corresponding author

Correspondence to Norbert Perrimon.

Supplementary information

  1. Supplementary Notes

    This file contains the Supplementary Methods, Supplementary Figures and Legends 1–6, Supplementary Notes, and six of nine Supplementary Tables of data discussed in the text. (PDF 3675 kb)

  2. Supplementary Table 1

    This file contains the complete list of hits from the primary RNAi screen, sorted by gene name, and including amplicon identifiers and Z-score at baseline and under insulin stimulus. This list can also be obtained at www.flyrnai.org. (XLS 190 kb)

  3. Supplementary Table 2

    This file contains the complete secondary screen validated gene list, sorted by gene name, and including amplicon identifiers (both original primary screen-scoring amplicon and secondary amplicon, if available), and the percent of negative control (luciferase) normalized dpERK signal under each condition tested. (XLS 86 kb)

  4. Supplementary Table 9

    This file contains the complete epistasis data for validated genes screened in RasV12 and Gap1 experiments (see Supplementary Methods for details). (XLS 53 kb)

  5. Supplementary Data

    This file contains Gene keywords associated with this study. (DOC 19 kb)

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