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Regulatory element detection using correlation with expression


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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Figure 1: Time courses for cell cycle and sporulation.


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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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Correspondence to Harmen J. Bussemaker.

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Bussemaker, H., Li, H. & Siggia, E. Regulatory element detection using correlation with expression. Nat Genet 27, 167–171 (2001).

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