Advertisement

Chemogenomic Approaches to Elucidation of Gene Function and Genetic Pathways

  • Sarah E. Pierce
  • Ronald W. Davis
  • Corey Nislow
  • Guri Giaever
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 548)

Summary

The ~6,000 strains in the yeast deletion collection can be studied in a single culture by using a microarray to detect the 20 bp DNA “barcodes” or “tags” contained in each strain. Barcode intensities measured by microarray are compared across time-points or across conditions to analyze the relative fitness of each strain. The development of this pooled fitness assay has greatly facilitated the functional annotation of the yeast genome by making genome-wide gene-deletion studies faster and easier, and has led to the development of high throughput methods for studying drug action in yeast. Pooled screens can be used for identifying gene functions, measuring the functional relatedness of gene pairs to group genes into pathways, identifying drug targets, and determining a drug’s mechanism of action. This process involves five main steps: preparing aliquots of pooled cells, pooled growth, isolation of genomic DNA and PCR amplification of the barcodes, array hybridization, and data analysis. In addition to yeast fitness applications, the general method of studying pooled samples with barcode arrays can also be adapted for use with other types of samples, such as mutant collections in other organisms, siRNA vectors, and molecular inversion probes.

Key words

S. cerevisiae Drug-target identification Functional assays Chemogenomics Gene networks Genomics DNA barcodes 

Notes

Acknowledgments

Work In the Giaever and Nislow labs is supported by the NHGRI, the Canadian Foundation for Innovation, and the CIHR (MOP-81340 to GG) and (MOP-84305 to CN).

References

  1. 1.
    Giaever, G. et al Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–91 (2002).PubMedCrossRefGoogle Scholar
  2. 2.
    Winzeler, E.A. et al. Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science 285, 901–6 (1999).PubMedCrossRefGoogle Scholar
  3. 3.
    Shoemaker, D.D., Lashkari, D.A., Morris, D., Mittmann, M. & Davis, R.W. Quantitative phenotypic analysis of yeast deletion mutants using a highly parallel molecular bar-coding strategy. Nat Genet 14, 450–6 (1996).PubMedCrossRefGoogle Scholar
  4. 4.
    Birrell, G.W. et al Transcriptional response of Saccharomyces cerevisiae to DNA-damaging agents does not identify the genes that protect against these agents. Proc Natl Acad Sci USA 99, 8778–83 (2002).PubMedCrossRefGoogle Scholar
  5. 5.
    Deutschbauer, A.M. et al Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast. Genetics 169, 1915–25 (2005).PubMedCrossRefGoogle Scholar
  6. 6.
    Giaever, G. et al Chemogenomic profiling: identifying the functional interactions of small molecules in yeast. Proc Natl Acad Sci USA 101, 793–8 (2004).PubMedCrossRefGoogle Scholar
  7. 7.
    Giaever, G. et al. Genomic profiling of drug sensitivities via induced haploinsufficiency. Nat Genet 21, 278–83 (1999).PubMedCrossRefGoogle Scholar
  8. 8.
    Kastenmayer, J.P. et al. Functional ­genomics of genes with small open reading frames (sORFs) in S. cerevisiae. Genome Res 16, 365–73 (2006).PubMedCrossRefGoogle Scholar
  9. 9.
    Lee, W. et al. Genome-wide requirements for resistance to functionally distinct DNA-damaging agents. PLoS Genet 1, e24 (2005).PubMedCrossRefGoogle Scholar
  10. 10.
    Lum, P.Y. et al Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes. Cell 116, 121–37 (2004).PubMedCrossRefGoogle Scholar
  11. 11.
    Ooi, S.L., Shoemaker, D.D. & Boeke, J.D. A DNA microarray-based genetic screen for nonhomologous end-joining mutants in Saccharomyces cerevisiae. Science 294, 2552–6 (2001).PubMedCrossRefGoogle Scholar
  12. 12.
    Parsons, A.B. et al Integration of chemical-genetic and genetic interaction data links bioactive compounds to cellular target pathways. Nat Biotechnol 22, 62–9 (2004).PubMedCrossRefGoogle Scholar
  13. 13.
    Parsons, A.B. et al Exploring the mode-of-action of bioactive compounds by chemical-genetic profiling in yeast. Cell 126, 611–25 (2006).PubMedCrossRefGoogle Scholar
  14. 14.
    Steinmetz, L.M. et al Systematic screen for human disease genes in yeast. Nat Genet 31, 400–4 (2002).PubMedGoogle Scholar
  15. 15.
    Hillenmeyer, M.E. et al The chemical genomic portrait of yeast: uncovering a phenotype for all genes. Science 320, 362–5 (2008).PubMedCrossRefGoogle Scholar
  16. 16.
    Hoon, S. et al An integrated platform of genome-wide assays reveals small molecule bioactivities. Nat Chem Biol 4(8), 498–506 (2008).PubMedCrossRefGoogle Scholar
  17. 17.
    Ericson, E. et al. Off-target effects of psychoactive drugs revealed by genome-wide assays in yeast. PLoS Genet 4(8), e1000151 (2008).PubMedCrossRefGoogle Scholar
  18. 18.
    Workman, C.T. et al A systems approach to mapping DNA damage response pathways. Science 312, 1054–9 (2006).PubMedCrossRefGoogle Scholar
  19. 19.
    Jensen, L.J., Jensen, T.S., de Lichtenberg, U., Brunak, S. & Bork, P. Co-evolution of transcriptional and post-translational cell-cycle regulation. Nature 443, 594–7 (2006).PubMedGoogle Scholar
  20. 20.
    Pollack, J.R. et al Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci USA 99, 12963–8 (2002).PubMedCrossRefGoogle Scholar
  21. 21.
    Groh, J.L., Luo, Q., Ballard, J.D. & Krumholz, L.R. A method adapting microarray technology for signature-tagged mutagenesis of Desulfovibrio desulfuricans G20 and Shewanella oneidensis MR-1 in anaerobic sediment survival experiments. Appl Environ Microbiol 71, 7064–74 (2005).PubMedCrossRefGoogle Scholar
  22. 22.
    Karlyshev, A.V. et al Application of high-density array-based signature-tagged muta­genesis to discover novel Yersinia virulence-associated genes. Infect Immun 69, 7810–9 (2001).PubMedCrossRefGoogle Scholar
  23. 23.
    Berns, K. et al A large-scale RNAi screen in human cells identifies new components of the p53 pathway. Nature 428, 431–7 (2004).PubMedCrossRefGoogle Scholar
  24. 24.
    Brummelkamp, T.R. et al An shRNA barcode screen provides insight into cancer cell vulnerability to MDM2 inhibitors. Nat Chem Biol 2, 202–6 (2006).PubMedCrossRefGoogle Scholar
  25. 25.
    Fischer, K.D. et al Defective T-cell receptor signalling and positive selection of Vav-deficient CD4 + CD8 + thymocytes. Nature 374, 474–7 (1995).PubMedCrossRefGoogle Scholar
  26. 26.
    Fraser, A. RNA interference: human genes hit the big screen. Nature 428, 375–8 (2004).PubMedCrossRefGoogle Scholar
  27. 27.
    Kolfschoten, I.G. et al A genetic screen identifies PITX1 as a suppressor of RAS activity and tumorigenicity. Cell 121, 849–58 (2005).PubMedCrossRefGoogle Scholar
  28. 28.
    Ngo, V.N. et al A loss-of-function RNA interference screen for molecular targets in cancer. Nature 441, 106–10 (2006).PubMedCrossRefGoogle Scholar
  29. 29.
    Ngo, V.N. et al A loss-of-function RNA interference screen for molecular targets in cancer. Nature 441, 106–10 (2006).PubMedCrossRefGoogle Scholar
  30. 30.
    Westbrook, T.F. et al A genetic screen for candidate tumor suppressors identifies REST. Cell 121, 837–48 (2005).PubMedCrossRefGoogle Scholar
  31. 31.
    Akhras, M.S. et al. PathogenMip assay: a multiplex pathogen detection assay. PLoS ONE 2, e223 (2007).PubMedCrossRefGoogle Scholar
  32. 32.
    Clayton, D.G. et al Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 37, 1243–6 (2005).PubMedCrossRefGoogle Scholar
  33. 33.
    Hardenbol, P. et al Multiplexed genotyping with sequence-tagged molecular inversion probes. Nat Biotechnol 21, 673–8 (2003).PubMedCrossRefGoogle Scholar
  34. 34.
    Hardenbol, P. et al Highly multiplexed molecular inversion probe genotyping: over 10,000 targeted SNPs genotyped in a single tube assay. Genome Res 15, 269–75 (2005).PubMedCrossRefGoogle Scholar
  35. 35.
    Pierce, S.E. et al A unique and universal molecular barcode array. Nat Methods 3, 601–3 (2006).PubMedCrossRefGoogle Scholar
  36. 36.
    Bolstad, B.M., Irizarry, R.A., Astrand, M. & Speed, T.P. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19, 185–93 (2003).PubMedCrossRefGoogle Scholar
  37. 37.
    Tusher, V.G., Tibshirani, R. & Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci USA 98, 5116–21 (2001).PubMedCrossRefGoogle Scholar
  38. 38.
    Pierce, S.E., Davis, R.W., Nislow, C., & Giaever, G. Genome-wide analysis of barcoded S. cerevisiae gene-deletion mutants in pooled cultures. Nat Protoc 2, 2958–74 (2007).PubMedCrossRefGoogle Scholar
  39. 39.
    Pan, X. et al A robust toolkit for functional profiling of the yeast genome. Mol Cell 16, 487–96 (2004).PubMedCrossRefGoogle Scholar
  40. 40.
    Yuan, D.S. et al. Improved microarray methods for profiling the Yeast Knockout strain collection. Nucleic Acids Res 33, e103 (2005).PubMedCrossRefGoogle Scholar
  41. 41.
    Tong, A.H. et al Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294, 2364–8 (2001).PubMedCrossRefGoogle Scholar
  42. 42.
    Tong, A.H. et al Global mapping of the yeast genetic interaction network. Science 303, 808–13 (2004).PubMedCrossRefGoogle Scholar
  43. 43.
    Davierwala, A.P. et al The synthetic genetic interaction spectrum of essential genes. Nat Genet 37, 1147–52 (2005).PubMedCrossRefGoogle Scholar
  44. 44.
    Schuldiner, M. et al Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–19 (2005).PubMedCrossRefGoogle Scholar
  45. 45.
    Stark, C. et al BioGRID: a general repository for interaction datasets. Nucleic Acids Res 34, D535–9 (2006).PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Sarah E. Pierce
    • 1
  • Ronald W. Davis
    • 1
  • Corey Nislow
    • 1
  • Guri Giaever
    • 1
  1. 1.Department of Pharmaceutical SciencesTerrence Donnelly Centre for Cellular and Biomolecular Research (CCBR), University of TorontoTorontoCanada M5S 3E1

Personalised recommendations