Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Analysis
  • Published:

Dosage suppression genetic interaction networks enhance functional wiring diagrams of the cell

Abstract

Dosage suppression is a genetic interaction in which overproduction of one gene rescues a mutant phenotype of another gene. Although dosage suppression is known to map functional connections among genes, the extent to which it might illuminate global cellular functions is unclear. Here we analyze a network of interactions linking dosage suppressors to 437 essential genes in yeast. For 424 genes, we curated interactions from the literature. Analyses revealed that many dosage suppression interactions occur between functionally related genes and that the majority do not overlap with other types of genetic or physical interactions. To confirm the generality of these network properties, we experimentally identified dosage suppressors for 29 genes from pooled populations of temperature-sensitive mutant cells transformed with a high-copy molecular-barcoded open reading frame library, MoBY-ORF 2.0. We classified 87% of the 1,640 total interactions into four general types of suppression mechanisms, which provided insight into their relative frequencies. This work suggests that integrating the results of dosage suppression studies with other interaction networks could generate insights into the functional wiring diagram of a cell.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Dosage suppression genetic interaction network for S. cerevisiae.
Figure 2: Properties of the yeast dosage suppression network.
Figure 3: A genetic requirement for PKA signaling in kinetochore function.
Figure 4: Decision tree used to categorize dosage suppression interactions.
Figure 5: Mechanisms of dosage suppression in yeast.

Similar content being viewed by others

Accession codes

Accessions

ArrayExpress

References

  1. Vavouri, T., Semple, J.I., Garcia-Verdugo, R. & Lehner, B. Intrinsic protein disorder and interaction promiscuity are widely associated with dosage sensitivity. Cell 138, 198–208 (2009).

    Article  CAS  Google Scholar 

  2. Sopko, R. et al. Mapping pathways and phenotypes by systematic gene overexpression. Mol. Cell 21, 319–330 (2006).

    Article  CAS  Google Scholar 

  3. Santarius, T., Shipley, J., Brewer, D., Stratton, M.R. & Cooper, C.S. A census of amplified and overexpressed human cancer genes. Nat. Rev. Cancer 10, 59–64 (2010).

    Article  CAS  Google Scholar 

  4. Jones, G.M. et al. A systematic library for comprehensive overexpression screens in Saccharomyces cerevisiae . Nat. Methods 5, 239–241 (2008).

    Article  CAS  Google Scholar 

  5. Moriya, H., Shimizu-Yoshida, Y. & Kitano, H. In vivo robustness analysis of cell division cycle genes in Saccharomyces cerevisiae . PLoS Genet. 2, e111 (2006).

    Article  Google Scholar 

  6. Kaizu, K., Moriya, H. & Kitano, H. Fragilities caused by dosage imbalance in regulation of the budding yeast cell cycle. PLoS Genet. 6, e1000919 (2010).

    Article  Google Scholar 

  7. Boone, C., Bussey, H. & Andrews, B.J. Exploring genetic interactions and networks with yeast. Nat. Rev. Genet. 8, 437–449 (2007).

    Article  CAS  Google Scholar 

  8. Rine, J. Gene overexpression in studies of Saccharomyces cerevisiae . Methods Enzymol. 194, 239–251 (1991).

    Article  CAS  Google Scholar 

  9. Prelich, G. Suppression mechanisms: themes from variations. Trends Genet. 15, 261–266 (1999).

    Article  CAS  Google Scholar 

  10. Dixon, S.J., Costanzo, M., Baryshnikova, A., Andrews, B. & Boone, C. Systematic mapping of genetic interaction networks. Annu. Rev. Genet. 43, 601–625 (2009).

    Article  CAS  Google Scholar 

  11. Costanzo, M. et al. The genetic landscape of a cell. Science 327, 425–431 (2010).

    Article  CAS  Google Scholar 

  12. Baryshnikova, A. et al. Quantitative analysis of fitness and genetic interactions in yeast on a genome scale. Nat. Methods 7, 1017–1024 (2010).

    Article  CAS  Google Scholar 

  13. Gavin, A.C. et al. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415, 141–147 (2002).

    Article  CAS  Google Scholar 

  14. Krogan, N.J. et al. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae . Nature 440, 637–643 (2006).

    Article  CAS  Google Scholar 

  15. Yu, H. et al. High-quality binary protein interaction map of the yeast interactome network. Science 322, 104–110 (2008).

    Article  CAS  Google Scholar 

  16. Tarassov, K. et al. An in vivo map of the yeast protein interactome. Science 320, 1465–1470 (2008).

    Article  CAS  Google Scholar 

  17. Zhu, J. et al. Integrating large-scale functional genomic data to dissect the complexity of yeast regulatory networks. Nat. Genet. 40, 854–861 (2008).

    Article  CAS  Google Scholar 

  18. Bender, A. & Pringle, J.R. Multicopy suppression of the cdc24 budding defect in yeast by CDC42 and three newly identified genes including the ras-related gene RSR1. Proc. Natl. Acad. Sci. USA 86, 9976–9980 (1989).

    Article  CAS  Google Scholar 

  19. Shimada, Y., Wiget, P., Gulli, M.P., Bi, E. & Peter, M. The nucleotide exchange factor Cdc24p may be regulated by auto-inhibition. EMBO J. 23, 1051–1062 (2004).

    Article  CAS  Google Scholar 

  20. Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

    Article  CAS  Google Scholar 

  21. van Dongen, S. A Cluster Algorithm for Graphs (National Research Institute for Mathematics and Computer Science in The Netherlands, Amsterdam, 2002).

  22. Myers, C.L., Barrett, D.R., Hibbs, M.A., Huttenhower, C. & Troyanskaya, O.G. Finding function: evaluation methods for functional genomic data. BMC Genomics 7, 187 (2006).

    Article  Google Scholar 

  23. Ma, H., Kunes, S., Schatz, P.J. & Botstein, D. Plasmid construction by homologous recombination in yeast. Gene 58, 201–216 (1987).

    Article  CAS  Google Scholar 

  24. Ho, C.H. et al. A molecular barcoded yeast ORF library enables mode-of-action analysis of bioactive compounds. Nat. Biotechnol. 27, 369–377 (2009).

    Article  CAS  Google Scholar 

  25. De Wulf, P., McAinsh, A.D. & Sorger, P.K. Hierarchical assembly of the budding yeast kinetochore from multiple subcomplexes. Genes Dev. 17, 2902–2921 (2003).

    Article  CAS  Google Scholar 

  26. Pagliuca, C., Draviam, V.M., Marco, E., Sorger, P.K. & De Wulf, P. Roles for the conserved spc105p/kre28p complex in kinetochore-microtubule binding and the spindle assembly checkpoint. PLoS ONE 4, e7640 (2009).

    Article  Google Scholar 

  27. Pramila, T., Wu, W., Miles, S., Noble, W.S. & Breeden, L.L. The Forkhead transcription factor Hcm1 regulates chromosome segregation genes and fills the S-phase gap in the transcriptional circuitry of the cell cycle. Genes Dev. 20, 2266–2278 (2006).

    Article  CAS  Google Scholar 

  28. Balciunas, D. & Ronne, H. Yeast genes GIS1–4: multicopy suppressors of the Gal- phenotype of snf1 mig1 srb8/10/11 cells. Mol. Gen. Genet. 262, 589–599 (1999).

    Article  CAS  Google Scholar 

  29. Li, J.M., Li, Y. & Elledge, S.J. Genetic analysis of the kinetochore DASH complex reveals an antagonistic relationship with the ras/protein kinase A pathway and a novel subunit required for Ask1 association. Mol. Cell. Biol. 25, 767–778 (2005).

    Article  CAS  Google Scholar 

  30. Tanaka, K. & Hirota, T. Chromosome segregation machinery and cancer. Cancer Sci. 100, 1158–1165 (2009).

    Article  CAS  Google Scholar 

  31. Toda, T. et al. Cloning and characterization of BCY1, a locus encoding a regulatory subunit of the cyclic AMP-dependent protein kinase in Saccharomyces cerevisiae . Mol. Cell. Biol. 7, 1371–1377 (1987).

    Article  CAS  Google Scholar 

  32. Klein, H.L. Spontaneous chromosome loss in Saccharomyces cerevisiae is suppressed by DNA damage checkpoint functions. Genetics 159, 1501–1509 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Hodgkin, J. Genetic suppression. WormBook 27, 1–13 (2005).

    Google Scholar 

  34. Reed, S.I., Hadwiger, J.A., Richardson, H.E. & Wittenberg, C. Analysis of the Cdc28 protein kinase complex by dosage suppression. J. Cell Sci. Suppl. 12, 29–37 (1989).

    Article  CAS  Google Scholar 

  35. Wittenberg, C., Sugimoto, K. & Reed, S.I. G1-specific cyclins of S. cerevisiae: cell cycle periodicity, regulation by mating pheromone, and association with the p34CDC28 protein kinase. Cell 62, 225–237 (1990).

    Article  CAS  Google Scholar 

  36. Aalto, M.K., Ronne, H. & Keranen, S. Yeast syntaxins Sso1p and Sso2p belong to a family of related membrane proteins that function in vesicular transport. EMBO J. 12, 4095–4104 (1993).

    Article  CAS  Google Scholar 

  37. Watts, F.Z., Shiels, G. & Orr, E. The yeast MYO1 gene encoding a myosin-like protein required for cell division. EMBO J. 6, 3499–3505 (1987).

    Article  CAS  Google Scholar 

  38. Rodriguez-Quinones, J.F. et al. Global mRNA expression analysis in myosin II deficient strains of Saccharomyces cerevisiae reveals an impairment of cell integrity functions. BMC Genomics 9, 34 (2008).

    Article  Google Scholar 

  39. Mani, R., St. Onge, R.P., Hartman, J.L. IV, Giaever, G. & Roth, F.P. Defining genetic interaction. Proc. Natl. Acad. Sci. USA 105, 3461–3466 (2008).

    Article  CAS  Google Scholar 

  40. St. Onge, R.P. et al. Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions. Nat. Genet. 39, 199–206 (2007).

    Article  CAS  Google Scholar 

  41. Gasch, A.P. et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241–4257 (2000).

    Article  CAS  Google Scholar 

  42. Gordon, C.L. & King, J. Genetic properties of temperature-sensitive folding mutants of the coat protein of phage P22. Genetics 136, 427–438 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Warner, J.R. & McIntosh, K.B. How common are extraribosomal functions of ribosomal proteins? Mol. Cell 34, 3–11 (2009).

    Article  CAS  Google Scholar 

  44. Haarer, B., Viggiano, S., Hibbs, M.A., Troyanskaya, O.G. & Amberg, D.C. Modeling complex genetic interactions in a simple eukaryotic genome: actin displays a rich spectrum of complex haploinsufficiencies. Genes Dev. 21, 148–159 (2007).

    Article  CAS  Google Scholar 

  45. Komili, S., Farny, N.G., Roth, F.P. & Silver, P.A. Functional specificity among ribosomal proteins regulates gene expression. Cell 131, 557–571 (2007).

    Article  CAS  Google Scholar 

  46. Ben-Aroya, S. et al. Toward a comprehensive temperature-sensitive mutant repository of the essential genes of Saccharomyces cerevisiae . Mol. Cell 30, 248–258 (2008).

    Article  CAS  Google Scholar 

  47. Li, Z. et al. Systematic exploration of essential yeast gene function with temperature-sensitive mutants. Nat. Biotechnol. 29, 361–367 (2011).

    Article  CAS  Google Scholar 

  48. Maere, S., Heymans, K. & Kuiper, M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21, 3448–3449 (2005).

    Article  CAS  Google Scholar 

  49. Butcher, R.A. & Schreiber, S.L. A microarray-based protocol for monitoring the growth of yeast overexpression strains. Nat. Protoc. 1, 569–576 (2006).

    Article  CAS  Google Scholar 

  50. Pierce, S.E. et al. A unique and universal molecular barcode array. Nat. Methods 3, 601–603 (2006).

    Article  CAS  Google Scholar 

  51. Lea, D.E. & Coulson, C.A. The distribution of the numbers of mutants in bacterial populations. J. Genet. 49, 264–285 (1949).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank S. Dixon for critical comments on the manuscript, M. Gebbia for microarray technical support, and C. Myers and J. Bellay for advice and data analysis support. L.M. was supported by a Canadian Institutes of Health Research (CIHR) doctoral research award. A.M.S. was supported by a University of Toronto open fellowship. J.S.C. and M.A.B. were supported by the Intramural Research Program of the US National Cancer Institute, US National Institutes of Health. G.G. was supported by the Canadian Cancer Society and the CIHR (research agreements 020380 and MOP-81340, respectively). C.N. was supported by the CIHR (MOP-84305). C.B. and B.A. were supported by Genome Canada through the Ontario Genomics Institute (2004-OGI-3-01). C.B. was supported by the CIHR (MOP-57830) and the Natural Sciences and Engineering Research Council of Canada (RGPIN 204899-06).

Author information

Authors and Affiliations

Authors

Contributions

L.M. was involved in MoBY-ORF construction, carried out experimental analysis and wrote the manuscript; C.H.H. was involved in MoBY-ORF construction, carried out experimental analysis and wrote the manuscript; S.L.B. was involved in MoBY-ORF construction and wrote the manuscript; W.J. and A.B. carried out computational analysis and wrote the manuscript; S.B. was involved in temperature-sensitive strain generation and carried out experimental analysis; A.M.S. and L.E.H. were involved in microarray data analysis; J.S.C. carried out the chromosome loss assays; E.K. and K.A. carried out experimental analysis and edited the manuscript; A.K. carried out experimental analysis; Z.L. was involved in temperature-sensitive strain generation; M.C. wrote the manuscript; M.A.B. edited the manuscript; G.G. and C.N. provided microarray data analysis and edited the manuscript; B.A. wrote the manuscript; C.B. conceived and planned the construction of the MoBY-ORF 2.0 library and wrote the manuscript.

Corresponding authors

Correspondence to Brenda Andrews or Charles Boone.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5 (PDF 694 kb)

Supplementary Table 1

Dosage suppression interactions curated in the Saccharomyces Genome Database. (XLS 410 kb)

Supplementary Table 2

Dosage suppression interactions identified in this study using the MoBY-ORF 2.0 library. (XLS 122 kb)

Supplementary Table 3

Gene pairs from this study tested for reciprocal suppression interactions. (XLS 20 kb)

Supplementary Table 4

Gene pairs annotated in the Saccharomyces Genome Database that show reciprocal suppression interactions. (XLS 27 kb)

Supplementary Table 5

Significant enrichment of yeast two-hybrid interactions in the dosage suppression interaction network. (XLS 12 kb)

Supplementary Table 6

Restriction digest fragments of MoBY-ORF 2.0 plasmids. (XLS 574 kb)

Supplementary Table 7

Yeast strains used in this study. (XLS 338 kb)

Supplementary Table 8

MoBY-ORF 2.0 plasmids used in this study. (XLS 38 kb)

Supplementary Data (ZIP 58 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Magtanong, L., Ho, C., Barker, S. et al. Dosage suppression genetic interaction networks enhance functional wiring diagrams of the cell. Nat Biotechnol 29, 505–511 (2011). https://doi.org/10.1038/nbt.1855

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.1855

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research