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Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae


Genomic and proteomic approaches can provide hypotheses concerning function for the large number of genes predicted from genome sequences1,2,3,4,5. Because of the artificial nature of the assays, however, the information from these high-throughput approaches should be considered with caution. Although it is possible that more meaningful hypotheses could be formulated by integrating the data from various functional genomic and proteomic projects6, it has yet to be seen to what extent the data can be correlated and how such integration can be achieved. We developed a 'transcriptome–interactome correlation mapping' strategy to compare the interactions between proteins encoded by genes that belong to common expression-profiling clusters with those between proteins encoded by genes that belong to different clusters. Using this strategy with currently available data sets for Saccharomyces cerevisiae, we provide the first global evidence that genes with similar expression profiles are more likely to encode interacting proteins. We show how this correlation between transcriptome and interactome data can be used to improve the quality of hypotheses based on the information from both approaches. The strategy described here may help to integrate other functional genomic and proteomic data, both in yeast and in higher organisms.

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Figure 1: A general strategy for transcriptome–interactome correlation mapping.
Figure 2: Transcriptome–interactome correlation maps.
Figure 3: Transcriptome–interactome correlation maps for sporulation and cell-stress data sets (see legend of Fig. 2).
Figure 4: Improved model from the integration of transcriptome and interactome data.


  1. Lockhart, D.J. & Winzeler, E.A. Genomics, gene expression and DNA arrays. Nature 405, 827–836 (2000).

    CAS  Article  Google Scholar 

  2. Pandey, A. & Mann, M. Proteomics to study genes and genomes. Nature 405, 837–846 (2000).

    CAS  Article  Google Scholar 

  3. Walhout, A.J.M. & Vidal, M. Protein interaction maps for model organisms. Nature Rev. Mol. Cell. Biol. 2, 55–62 (2001).

    CAS  Article  Google Scholar 

  4. Kumar, A. & Snyder, M. Emerging technologies in yeast genomics. Nature Rev. Genet. 2, 302–312 (2001).

    CAS  Article  Google Scholar 

  5. Sternberg, P.W. Working in the post-genomic C. elegans world. Cell 105, 173–176 (2001).

    CAS  Article  Google Scholar 

  6. Vidal, M. A biological atlas of functional maps. Cell 104, 333–339 (2001).

    CAS  Article  Google Scholar 

  7. Eisen, M.B., Spellman, P.T., Brown, P.O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA 95, 14863–14868 (1998).

    CAS  Article  Google Scholar 

  8. Tavazoie, S., Hughes, J.D., Campbell, M.J., Cho, R.J. & Church, G.M. Systematic determination of genetic network architecture. Nature Genet. 22, 281–285 (1999).

    CAS  Article  Google Scholar 

  9. Hartigan, J.A. Clustering Algorithms (Wiley, New York, 1975).

    Google Scholar 

  10. Cho, R.J. et al. A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell 2, 65–73 (1998).

    CAS  Article  Google Scholar 

  11. Hodges, P.E., McKee, A.H., Davis, B.P., Payne, W.E. & Garrels, J.I. The Yeast Proteome Database (YPD): a model for the organization and presentation of genome-wide functional data. Nucleic Acids Res. 27, 69–73 (1999).

    CAS  Article  Google Scholar 

  12. Mewes, H.W. et al. MIPS: a database for genomes and protein sequences. Nucleic Acids Res. 28, 37–40 (2000).

    CAS  Article  Google Scholar 

  13. Uetz, P. et al. A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae. Nature 403, 623–627 (2000).

    CAS  Article  Google Scholar 

  14. Ito, T. et al. Toward a protein–protein interaction map of the budding yeast: a comprehensive system to examine two-hybrid interactions in all possible combinations between yeast proteins. Proc. Natl Acad. Sci. USA 97, 1143–1147 (2000).

    CAS  Article  Google Scholar 

  15. Ito, T. et al. A comprehensive two-hybrid analysis to explore the yeast protein interactome. Proc. Natl Acad. Sci. USA 98, 4569–4574 (2001).

    CAS  Article  Google Scholar 

  16. Primig, M. et al. The core meiotic transcriptome in budding yeasts. Nature Genet. 26, 415–423 (2000).

    CAS  Article  Google Scholar 

  17. Jelinsky, S.A., Estep, P., Church, G.M. & Samson, L.D. Regulatory networks revealed by transcriptional profiling of damaged Saccharomyces cerevisiae cells: Rpn4 links base excision repair with proteasomes. Mol. Cell. Biol. 20, 8157–8167 (2000).

    CAS  Article  Google Scholar 

  18. Padilla, P.A., Fuge, E.K., Crawford, M.E., Errett, A. & Werner-Washburne, M. The highly conserved, coregulated SNO and SNZ gene families in Saccharomyces cerevisiae respond to nutrient limitation. J. Bacteriol. 180, 5718–5726 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

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We thank P. Lansburry for his support, Mr. and Ms. Fu for their financial help, R.E. Esposito for exchange of information, V. Rebel and members of the Vidal lab for insightful suggestions and M. Walhout, T. Brüls and N. Thierry-Mieg for reading the manuscript. This work was supported by grant 1 RO1 HG01715-01 from the National Human Genome Research Institute, awarded to M.V.

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Correspondence to Marc Vidal.

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Ge, H., Liu, Z., Church, G. et al. Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae. Nat Genet 29, 482–486 (2001).

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