Abstract
We present here a new computational method for discovering cis-regulatory elements that circumvents the need to cluster genes based on their expression profiles. Based on a model in which upstream motifs contribute additively to the log-expression level of a gene, this method requires a single genome-wide set of expression ratios and the upstream sequence for each gene, and outputs statistically significant motifs. Analysis of publicly available expression data for Saccharomyces cerevisiae reveals several new putative regulatory elements, some of which plausibly control the early, transient induction of genes during sporulation. Known motifs generally have high statistical significance.
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References
Cherry, J.M. et al. Genetic and physical maps of Saccharomyces cerevisiae. Nature 387, 67–73 (1997).
Schena, M., Shalon, D., Davis, R.W. & Brown, P.O. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470 (1995).
Lockhart, D.J. et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nature Biotechnol. 14, 1675–1680 (1996).
Velculescu, V.E., Zhang, L., Vogelstein, B. & Kinzler, K.W. Serial analysis of gene expression. Science 270, 484–487 (1995).
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).
Roth, F.R., Hughes, J.D., Estep, P.W. & Church, G.M. Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation. Nature Biotechnol. 16, 939–945 (1998).
Lawrence, C.E. et al. Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science 262, 208–214 (1993).
Neuwald, A.F., Liu, J.S. & Lawrence, C.E. Gibbs motif sampling: detection of bacterial outer membrane protein repeats. Protein Sci. 4, 1618–1632 (1995).
Van Helden, J., Andre, B. & Collado-Vides, J. Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies. J. Mol. Biol. 281, 827–842 (1998).
DeRisi, J.L., Iyer, V.R. & Brown, P.O. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 287, 680–686 (1997).
Chu, S. et al. The transcriptional program of sporulation in budding yeast. Science 282, 699–705 (1998).
Cho, R.J. et al. A genome-wide transcriptional analysis of the mitotic cell cycle. Mol. Cell 2, 65–73 (1998).
Spellman, P.T. et al. Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. Mol. Biol. Cell. 9, 3273–3297 (1998).
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).
Berg, O.G. & Von Hippel, P.H. Selection of DNA binding sites by regulatory proteins. Statistical-mechanical theory and application to operators and promoters. J. Mol. Biol. 193, 723–750 (1987).
Magasanik, B. Regulation of nitrogen utilisation. in The Molecular and Cellular Biology of the Yeast Saccharomyces: Gene Expression (eds. Jones, E.W., Pringle, J.R. & Broach, J.R.) 283–318 (Cold Spring Harbor Laboratory Press, Cold Spring Harbor, 1992).
Niehrs, C. & Pollet, N. Synexpression groups in eukaryotes. Nature 402, 483–487 (1999).
Ptashne, M. & Gann, A. Imposing specificity by localization: mechanism and evolvability. Curr. Biol. 8, R897 (1998).
Holstege, F.C.P. et al. Dissecting the regulatory circuitry of a eukaryotic genome. Cell 95, 717–728 (1998).
Halfter, H., Kavety, B., Vandekerckhove, J., Kiefer, F. & Gallwitz, D. Sequence, expression and mutational analysis of BAF1, a transcriptional activator and ARS1-binding protein of the yeast Saccharomyces cerevisiae. EMBO J. 8, 4265–4272 (1989).
Della Seta, F. et al. The ABF1 factor is the transcriptional activator of the L2 ribosomal 15 protein genes in Saccharomyces cerevisiae. Mol. Cell. Biol. 10, 2437–2441 (1990).
Loots, G.G. et al. Identification of a coordinate regulator of interleukins 4, 13, and 5 by cross-species sequence comparisons. Science 288, 136–140 (2000).
Hardison, R.C., Oeltjen, J. & Miller, W. Long human-mouse sequence alignments reveal novel regulatory elements: a reason to sequence the mouse genome. Genome Res. 7, 959–966 (1997).
Ben-Dor, A., Shamir, R. & Yakhini, Z. Clustering gene expression patterns. J. Comput. Biol. 6, 281–297 (1999).
Acknowledgements
We thank B. Shraiman for suggesting linear multivariate fits to expression data, and L. Grivell, R. Lascaris and H. de Nobel for discussions and critical reading of the manuscript. Support was received from the NSF under grant number DMR 9732083 and from the Keck foundation to H.L.
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Bussemaker, H., Li, H. & Siggia, E. Regulatory element detection using correlation with expression. Nat Genet 27, 167–171 (2001). https://doi.org/10.1038/84792
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DOI: https://doi.org/10.1038/84792
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