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Identifying regulatory networks by combinatorial analysis of promoter elements

Nature Genetics volume 29, pages 153–159 (2001)Cite this article

Abstract

Several computational methods based on microarray data are currently used to study genome-wide transcriptional regulation. Few studies, however, address the combinatorial nature of transcription, a well-established phenomenon in eukaryotes. Here we describe a new approach using microarray data to uncover novel functional motif combinations in the promoters of Saccharomyces cerevisiae. In addition to identifying novel motif combinations that affect expression patterns during the cell cycle, sporulation and various stress responses, we observed regulatory cross-talk among several of these processes. We have also generated motif-association maps that provide a global view of transcription networks. The maps are highly connected, suggesting that a small number of transcription factors are responsible for a complex set of expression patterns in diverse conditions. This approach may be useful for modeling transcriptional regulatory networks in more complex eukaryotes.

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Figure 1: a, Strategy used to discover and analyze synergistic motif combinations.
Figure 2: The effect of relative motif orientation on motif synergy.
Figure 3: Global motif synergy map.
Figure 4: Combinograms of cell-cycle- and sporulation-related motifs.
Figure 5: Combinograms of the heat-shock16 and the nucleotide excision repair18 experiments.

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Acknowledgements

We thank J. Hughes for providing many of the motifs used in these analyses and U. Keich for assistance with the statistical analyses of motif synergies. We are grateful to J. Aach, B. Cohen, A. Derti, P. D'Haeseleer, A. Dudley, M. Kupiec, R. Mitra, F. Roth, D. Segré and M. Wright for advice and suggestions. Y.P. was a scholar of the Fulbright Foundation. We are grateful to the US Department of Energy and National Science Foundation and to the Lipper Foundation for grant support.

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Author notes

  1. Yitzhak Pilpel and Priya Sudarsanam: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Genetics and Lipper Center for Computational Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Yitzhak Pilpel, Priya Sudarsanam & George M. Church

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  1. Yitzhak Pilpel
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Correspondence to George M. Church.

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Pilpel, Y., Sudarsanam, P. & Church, G. Identifying regulatory networks by combinatorial analysis of promoter elements. Nat Genet 29, 153–159 (2001). https://doi.org/10.1038/ng724

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