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Quantitative analysis of triple-mutant genetic interactions

Nature Protocols volume 9, pages 1867–1881 (2014)Cite this article

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Abstract

The quantitative analysis of genetic interactions between pairs of gene mutations has proven to be effective for characterizing cellular functions, but it can miss important interactions for functionally redundant genes. To address this limitation, we have developed an approach termed triple-mutant analysis (TMA). The procedure relies on a query strain that contains two deletions in a pair of redundant or otherwise related genes, which is crossed against a panel of candidate deletion strains to isolate triple mutants and measure their growth. A central feature of TMA is to interrogate mutants that are synthetically sick when two other genes are deleted but interact minimally with either single deletion. This approach has been valuable for discovering genes that restore critical functions when the principal actors are deleted. TMA has also uncovered double-mutant combinations that produce severe defects because a third protein becomes deregulated and acts in a deleterious fashion, and it has revealed functional differences between proteins presumed to act together. The protocol is optimized for Singer ROTOR pinning robots, takes 3 weeks to complete and measures interactions for up to 30 double mutants against a library of 1,536 single mutants.

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Figure 1: Schematic of workflow for the generation of triple mutants.
Figure 2: Negative genetic interactions revealed by TMA.
Figure 3: Positive genetic interactions revealed by TMA.
Figure 4: TMA can reveal differences between collaborative components.
Figure 5: MinDC highlights triple-mutant interactions that differ markedly from the corresponding double-mutant interactions.
Figure 6: Schematic of plate replications during ROTOR pinning steps.
Figure 7: Image of a high-density yeast plate generated in a TMA screen.
Figure 8: Clustering and visualization of TMA data.

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References

  1. Tong, A.H. et al. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294, 2364–2368 (2001).

    Article  CAS  Google Scholar 

  2. Tong, A.H. et al. Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004).

    Article  CAS  Google Scholar 

  3. Collins, S.R., Roguev, A. & Krogan, N.J. Quantitative genetic interaction mapping using the E-MAP approach. Methods Enzymol. 470, 205–231 (2010).

    Article  CAS  Google Scholar 

  4. Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).

    Article  CAS  Google Scholar 

  5. Butland, G. et al. eSGA: E. coli. synthetic genetic array analysis. Nat. Methods 5, 789–795 (2008).

    Article  CAS  Google Scholar 

  6. Typas, A. et al. High-throughput, quantitative analyses of genetic interactions in E. coli. Nat. Methods 5, 781–787 (2008).

    Article  CAS  Google Scholar 

  7. Bassik, M.C. et al. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell 152, 909–922 (2013).

    Article  CAS  Google Scholar 

  8. Roguev, A. et al. Quantitative genetic-interaction mapping in mammalian cells. Nat. Methods 10, 432–437 (2013).

    Article  CAS  Google Scholar 

  9. Roguev, A., Wiren, M., Weissman, J.S. & Krogan, N.J. High-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe. Nat. Methods 4, 861–866 (2007).

    Article  CAS  Google Scholar 

  10. Ryan, C.J. et al. Hierarchical modularity and the evolution of genetic interactomes across species. Mol. Cell 46, 691–704 (2012).

    Article  CAS  Google Scholar 

  11. Pan, X. et al. A robust toolkit for functional profiling of the yeast genome. Mol. Cell 16, 487–496 (2004).

    Article  CAS  Google Scholar 

  12. Pan, X. et al. A DNA integrity network in the yeast Saccharomyces cerevisiae. Cell 124, 1069–1081 (2006).

    Article  CAS  Google Scholar 

  13. Aguilar, P.S. et al. A plasma-membrane E-MAP reveals links of the eisosome with sphingolipid metabolism and endosomal trafficking. Nat. Struct. Mol. Biol. 17, 901–908 (2010).

    Article  CAS  Google Scholar 

  14. Collins, S.R. et al. Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature 446, 806–810 (2007).

    Article  CAS  Google Scholar 

  15. Fiedler, D. et al. Functional organization of the S. cerevisiae phosphorylation network. Cell 136, 952–963 (2009).

    Article  CAS  Google Scholar 

  16. Wilmes, G.M. et al. A genetic interaction map of RNA-processing factors reveals links between Sem1/Dss1-containing complexes and mRNA export and splicing. Mol. Cell 32, 735–746 (2008).

    Article  CAS  Google Scholar 

  17. Schuldiner, M., Collins, S.R., Weissman, J.S. & Krogan, N.J. Quantitative genetic analysis in Saccharomyces cerevisiae using epistatic miniarray profiles (E-MAPs) and its application to chromatin functions. Methods 40, 344–352 (2006).

    Article  CAS  Google Scholar 

  18. Braberg, H. et al. From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II. Cell 154, 775–788 (2013).

    Article  CAS  Google Scholar 

  19. Surma, M.A. et al. A lipid E-MAP identifies Ubx2 as a critical regulator of lipid saturation and lipid bilayer stress. Mol. Cell 51, 519–530 (2013).

    Article  CAS  Google Scholar 

  20. Beltrao, P., Cagney, G. & Krogan, N.J. Quantitative genetic interactions reveal biological modularity. Cell 141, 739–745 (2010).

    Article  CAS  Google Scholar 

  21. Donaldson, A.D. The yeast mitotic cyclin Clb2 cannot substitute for S-phase cyclins in replication origin firing. EMBO Rep. 1, 507–512 (2000).

    Article  CAS  Google Scholar 

  22. Haber, J.E. et al. Systematic triple-mutant analysis uncovers functional connectivity between pathways involved in chromosome regulation. Cell Rep. 3, 2168–2178 (2013).

    Article  CAS  Google Scholar 

  23. Mai, B. & Breeden, L. CLN1 and its repression by Xbp1 are important for efficient sporulation in budding yeast. Mol. Cell Biol. 20, 478–487 (2000).

    Article  CAS  Google Scholar 

  24. Segal, M., Clarke, D.J. & Reed, S.I. Clb5-associated kinase activity is required early in the spindle pathway for correct preanaphase nuclear positioning in Saccharomyces cerevisiae. J. Cell Biol. 143, 135–145 (1998).

    Article  CAS  Google Scholar 

  25. Hsu, W.S. et al. S-phase cyclin-dependent kinases promote sister chromatid cohesion in budding yeast. Mol. Cell Biol. 31, 2470–2483 (2011).

    Article  CAS  Google Scholar 

  26. Ben-Aroya, S., Koren, A., Liefshitz, B., Steinlauf, R. & Kupiec, M. ELG1, a yeast gene required for genome stability, forms a complex related to replication factor C. Proc. Natl. Acad. Sci. USA 100, 9906–9911 (2003).

    Article  CAS  Google Scholar 

  27. Green, C.M., Erdjument-Bromage, H., Tempst, P. & Lowndes, N.F. A novel Rad24 checkpoint protein complex closely related to replication factor C. Curr. Biology 10, 39–42 (2000).

    Article  CAS  Google Scholar 

  28. Hanna, J.S., Kroll, E.S., Lundblad, V. & Spencer, F.A. Saccharomyces cerevisiae CTF18 and CTF4 are required for sister chromatid cohesion. Mol. Cell Biol. 21, 3144–3158 (2001).

    Article  CAS  Google Scholar 

  29. Mayer, M.L., Gygi, S.P., Aebersold, R. & Hieter, P. Identification of RFC(Ctf18p, Ctf8p, Dcc1p): an alternative RFC complex required for sister chromatid cohesion in S. cerevisiae. Mol. Cell 7, 959–970 (2001).

    Article  CAS  Google Scholar 

  30. Naiki, T., Kondo, T., Nakada, D., Matsumoto, K. & Sugimoto, K. Chl12 (Ctf18) forms a novel replication factor C-related complex and functions redundantly with Rad24 in the DNA replication checkpoint pathway. Mol. Cell Biol. 21, 5838–5845 (2001).

    Article  CAS  Google Scholar 

  31. Roelofs, J. et al. Chaperone-mediated pathway of proteasome regulatory particle assembly. Nature 459, 861–865 (2009).

    Article  CAS  Google Scholar 

  32. De Koning, L., Corpet, A., Haber, J.E. & Almouzni, G. Histone chaperones: an escort network regulating histone traffic. Nat. Struct. Mol. Biol. 14, 997–1007 (2007).

    Article  CAS  Google Scholar 

  33. Enomoto, S. & Berman, J. Chromatin assembly factor I contributes to the maintenance, but not the re-establishment, of silencing at the yeast silent mating loci. Genes Dev. 12, 219–232 (1998).

    Article  CAS  Google Scholar 

  34. Ramey, C.J. et al. Activation of the DNA damage checkpoint in yeast lacking the histone chaperone anti-silencing function 1. Mol. Cell Biol. 24, 10313–10327 (2004).

    Article  CAS  Google Scholar 

  35. Sugawara, N., Wang, X. & Haber, J.E. In vivo roles of Rad52, Rad54, and Rad55 proteins in Rad51-mediated recombination. Mol. Cell 12, 209–219 (2003).

    Article  CAS  Google Scholar 

  36. Driscoll, R., Hudson, A. & Jackson, S.P. Yeast Rtt109 promotes genome stability by acetylating histone H3 on lysine 56. Science 315, 649–652 (2007).

    Article  CAS  Google Scholar 

  37. Han, J., Zhou, H., Li, Z., Xu, R.M. & Zhang, Z. Acetylation of lysine 56 of histone H3 catalyzed by RTT109 and regulated by ASF1 is required for replisome integrity. J. Biol. Chem. 282, 28587–28596 (2007).

    Article  CAS  Google Scholar 

  38. Blanco, M.G., Matos, J., Rass, U., Ip, S.C. & West, S.C. Functional overlap between the structure-specific nucleases Yen1 and Mus81-Mms4 for DNA-damage repair in S. cerevisiae. DNA Repair 9, 394–402 (2010).

    Article  CAS  Google Scholar 

  39. Ho, C.K., Mazon, G., Lam, A.F. & Symington, L.S. Mus81 and Yen1 promote reciprocal exchange during mitotic recombination to maintain genome integrity in budding yeast. Mol. Cell 40, 988–1000 (2010).

    Article  CAS  Google Scholar 

  40. Tay, Y.D. & Wu, L. Overlapping roles for Yen1 and Mus81 in cellular Holliday junction processing. J. Biol. Chem. 285, 11427–11432 (2010).

    Article  CAS  Google Scholar 

  41. Zhao, X., Muller, E.G. & Rothstein, R. A suppressor of two essential checkpoint genes identifies a novel protein that negatively affects dNTP pools. Mol. Cell 2, 329–340 (1998).

    Article  CAS  Google Scholar 

  42. Koranda, M., Schleiffer, A., Endler, L. & Ammerer, G. Forkhead-like transcription factors recruit Ndd1 to the chromatin of G2/M-specific promoters. Nature 406, 94–98 (2000).

    Article  CAS  Google Scholar 

  43. Jinek, M. et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

    Article  CAS  Google Scholar 

  44. Boulton, S.J. & Jackson, S.P. Identification of a Saccharomyces cerevisiae Ku80 homologue: roles in DNA double strand break rejoining and in telomeric maintenance. Nucleic Acids Res. 24, 4639–4648 (1996).

    Article  CAS  Google Scholar 

  45. Lee, S.E., Paques, F., Sylvan, J. & Haber, J.E. Role of yeast SIR genes and mating type in directing DNA double-strand breaks to homologous and non-homologous repair paths. Curr. Biol. 9, 767–770 (1999).

    Article  CAS  Google Scholar 

  46. Moore, J.K. & Haber, J.E. Cell cycle and genetic requirements of two pathways of nonhomologous end-joining repair of double-strand breaks in Saccharomyces cerevisiae. Mol. Cell Biol. 16, 2164–2173 (1996).

    Article  CAS  Google Scholar 

  47. Ma, J.L., Kim, E.M., Haber, J.E. & Lee, S.E. Yeast Mre11 and Rad1 proteins define a Ku-independent mechanism to repair double-strand breaks lacking overlapping end sequences. Mol. Cell Biol. 23, 8820–8828 (2003).

    Article  CAS  Google Scholar 

  48. Laufer, C., Fischer, B., Billmann, M., Huber, W. & Boutros, M. Mapping genetic interactions in human cancer cells with RNAi and multiparametric phenotyping. Nat. Methods 10, 427–431 (2013).

    Article  CAS  Google Scholar 

  49. Deriano, L. & Roth, D.B. Modernizing the nonhomologous end-joining repertoire: alternative and classical NHEJ share the stage. Annu. Rev. Genet. 47, 433–455 (2013).

    Article  CAS  Google Scholar 

  50. Collins, S.R., Schuldiner, M., Krogan, N.J. & Weissman, J.S. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7, R63 (2006).

    Article  Google Scholar 

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Acknowledgements

We thank S. Bohn for helpful discussion and comments. This work was supported by grants from the US National Institutes of Health (GM084448, GM084279, GM081879 and GM098101 to N.J.K., and GM61766, GM76020 and GM20056 to J.E.H.). N.J.K. is a Searle Scholar and a Keck Young Investigator.

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Authors and Affiliations

  1. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA

    Hannes Braberg, Richard Alexander, Michael Shales, Jiewei Xu, Kathleen E Franks-Skiba & Nevan J Krogan

  2. California Institute for Quantitative Biosciences (QB3), San Francisco, California, USA

    Hannes Braberg, Richard Alexander, Michael Shales, Jiewei Xu, Kathleen E Franks-Skiba & Nevan J Krogan

  3. Department of Biology and Rosenstiel Basic Medical Sciences Research Center, Brandeis University, Waltham, Massachusetts, USA

    Qiuqin Wu & James E Haber

  4. J. David Gladstone Institutes, San Francisco, California, USA

    Nevan J Krogan

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Contributions

H.B., R.A., J.E.H. and N.J.K. designed the procedure; and H.B., R.A., M.S., J.X., K.E.F.-S., Q.W., J.E.H. and N.J.K. wrote the manuscript.

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Correspondence to James E Haber or Nevan J Krogan.

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Braberg, H., Alexander, R., Shales, M. et al. Quantitative analysis of triple-mutant genetic interactions. Nat Protoc 9, 1867–1881 (2014). https://doi.org/10.1038/nprot.2014.127

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