Brief Communication | Published:

A bioinformatics method identifies prominent off-targeted transcripts in RNAi screens

Nature Methods volume 9, pages 363366 (2012) | Download Citation

Abstract

Because off-target effects hamper interpretation and validation of RNAi screen data, we developed a bioinformatics method, genome-wide enrichment of seed sequence matches (GESS), to identify candidate off-targeted transcripts in primary screening data. GESS analysis revealed a prominent off-targeted transcript in several screens, including MAD2 (MAD2L1) in a screen for genes required for the spindle assembly checkpoint. GESS analysis results can enhance the validation rate in RNAi screens.

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Acknowledgements

We thank members of the Institute of Chemistry and Cell Biology and C. Shamu for providing siRNA sequences for hits from the Eg5-inhibitor RNAi screen as well as the use of facility equipment for our screening experiments, S. Natesan and P. August for helpful discussions in early stages of this work, S. Elledge for helpful discussions and for critical reading of the manuscript and J. Ware at the Harvard Catalyst Biostatistics consulting group for help in devising the statistical analysis workflow in the present manuscript. Funding for statistical analysis was supported in part by grant 1 UL1 RR025758-01, Harvard Clinical and Translational Science Center, from the US National Center for Research Resources; the content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the US National Institutes of Health. This research was funded by a Sanofi-Aventis grant and US National Institutes of Health grant GM66492 to R.W.K.

Author information

Author notes

    • Susan Lyman
    • , Jeremy F Huckins
    •  & Brian Quattrochi

    Present addresses: Gilead Sciences, Inc., Foster City, California, USA (S.L.), Department of Psychology and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA (J.F.H.) and Center for Academy Achievements, University of Massachusetts Medical School, Worcester, Massachusetts, USA (B.Q.).

Affiliations

  1. Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA.

    • Frederic D Sigoillot
    • , Susan Lyman
    • , Jeremy F Huckins
    • , Eunah Chung
    • , Brian Quattrochi
    •  & Randall W King
  2. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.

    • Britt Adamson

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Contributions

F.D.S., S.L. and R.W.K. conceived the study. F.D.S., S.L., E.C., B.Q. and B.A. performed the experiments. F.D.S. and J.F.H. wrote the GESS program code. F.D.S. and R.W.K. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Randall W King.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–12, Supplementary Tables 1–3, Supplementary Results 1–4

Zip files

  1. 1.

    Supplementary Data 1

    All siRNA sequences and associated phenotype data files analyzed in this report are provided as a compressed archive file.

  2. 2.

    Supplementary Data 2

    All GESS analysis result excel files are provided as a compressed archive file.

  3. 3.

    Supplementary Data 3

    Transcript sequence databases for the human and mouse genomes.

  4. 4.

    Supplementary Software 1

    GESS standalone package with manual, Windows 32-bit.

  5. 5.

    Supplementary Software 2

    GESS standalone package with manual, Windows 64-bit.

  6. 6.

    Supplementary Software 3

    GESS standalone package with manual, Linux 32-bit.

  7. 7.

    Supplementary Software 4

    GESS standalone package with manual, Linux 64-bit.

  8. 8.

    Supplementary Software 5

    GESS standalone package with manual, Mac.

About this article

Publication history

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DOI

https://doi.org/10.1038/nmeth.1898

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