Abstract

Combinatorial genetic screening using CRISPR–Cas9 is a useful approach to uncover redundant genes and to explore complex gene networks. However, current methods suffer from interference between the single-guide RNAs (sgRNAs) and from limited gene targeting activity. To increase the efficiency of combinatorial screening, we employ orthogonal Cas9 enzymes from Staphylococcus aureus and Streptococcus pyogenes. We used machine learning to establish S. aureus Cas9 sgRNA design rules and paired S. aureus Cas9 with S. pyogenes Cas9 to achieve dual targeting in a high fraction of cells. We also developed a lentiviral vector and cloning strategy to generate high-complexity pooled dual-knockout libraries to identify synthetic lethal and buffering gene pairs across multiple cell types, including MAPK pathway genes and apoptotic genes. Our orthologous approach also enabled a screen combining gene knockouts with transcriptional activation, which revealed genetic interactions with TP53. The “Big Papi” (paired aureus and pyogenes for interactions) approach described here will be widely applicable for the study of combinatorial phenotypes.

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Acknowledgements

We thank S. Elmore and G. Wei for helpful discussions; E. Sukharevsky, R. Hanna, and I. Sebenius for experimental assistance and comments on the manuscript; D. Ortiz for emotional uplift. We thank T. Hart and other anonymous referees for helpful comments during the review process. F.J.N. is supported by a cellular and developmental biology training grant (NIH T32GM007226-41). J.G.D. is supported by the Next Generation Fund at the Broad Institute of MIT and Harvard. This work was supported by the Functional Genomics Consortium (D.E.R.)., Starr Cancer Consortium (B.E.B.), and National Cancer Institute–NIH Common Fund (DP1CA216873) (B.E.B.).

Author information

Author notes

    • Fadi J Najm
    • , Christine Strand
    • , Katherine F Donovan
    • , Mudra Hegde
    •  & Kendall R Sanson

    These authors contributed equally to this work.

Affiliations

  1. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

    • Fadi J Najm
    • , Christine Strand
    • , Katherine F Donovan
    • , Mudra Hegde
    • , Kendall R Sanson
    • , Emma W Vaimberg
    • , Meagan E Sullender
    • , Ella Hartenian
    • , Zohra Kalani
    • , Scott T Younger
    • , Bradley E Bernstein
    • , David E Root
    •  & John G Doench
  2. Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

    • Fadi J Najm
    •  & Bradley E Bernstein
  3. Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

    • Fadi J Najm
    •  & Bradley E Bernstein
  4. Microsoft Research New England, Cambridge, Massachusetts, USA.

    • Nicolo Fusi
    •  & Jennifer Listgarten

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Contributions

F.J.N., C.S., K.F.D., K.R.S., Z.K., E.W.V., M.E.S., E.H., and J.G.D. designed and performed experiments. N.F. and J.L. performed the computational modeling of SaCas9 activity. M.H., S.T.Y., and J.G.D. analyzed screening data. B.E.B. and D.E.R. provided senior guidance. F.J.N., D.E.R., and J.G.D. wrote the manuscript with assistance from other authors.

Competing interests

J.L. and N.F. are employed by Microsoft Research. J.G.D. consults for Tango Therapeutics.

Corresponding author

Correspondence to John G Doench.

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