Genomic analysis of regulatory network dynamics reveals large topological changes (original) (raw)

Nature volume 431, pages 308–312 (2004) Cite this article

Abstract

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically1,2,3,4,5,6,7,8. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information9,10,11 and gene-expression data12,13,14,15,16 for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here—particularly the large-scale topological changes and hub transience—will apply to other biological networks, including complex sub-systems in higher eukaryotes.

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Acknowledgements

We thank P. Bertone, N. Domedel-Puig, E. Hovig, R. Jansen, K. Kleivi, G. Koentges, E. Koonin, B. Lenhard, A. Paccanaro, J. Rozowsky, J. Tegner, V. Trifonov, A. Todd, Y. Xia and H. Zao for comments on the paper. N.M.L. thanks the Anna Fuller Fund and the MRC LMB Visitor's Program. M.M.B. acknowledges financial support from the Cambridge Commonwealth Trust, Trinity College, Cambridge and the MRC LMB. M.G. is supported by the NSF and NIH.

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Author notes

  1. Nicholas M. Luscombe and M. Madan Babu: These authors contributed equally to this work

Authors and Affiliations

  1. Department of Molecular Biophysics and Biochemistry, Yale University, PO Box 208114, New Haven, Connecticut, 06520-8114, USA
    Nicholas M. Luscombe, Haiyuan Yu & Mark Gerstein
  2. Department of Molecular, Cellular and Developmental Biology, Yale University, PO Box 208114, New Haven, Connecticut, 06520-8114, USA
    Michael Snyder
  3. Department of Computer Science, Yale University, PO Box 208114, New Haven, Connecticut, 06520-8114, USA
    Mark Gerstein
  4. Division of Structural Studies, MRC Laboratory of Molecular Biology, Hills Road, Cambridge, CB2 2QH, UK
    M. Madan Babu & Sarah A. Teichmann

Authors

  1. Nicholas M. Luscombe
  2. M. Madan Babu
  3. Haiyuan Yu
  4. Michael Snyder
  5. Sarah A. Teichmann
  6. Mark Gerstein

Corresponding authors

Correspondence toNicholas M. Luscombe, M. Madan Babu, Sarah A. Teichmann or Mark Gerstein.

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The authors declare that they have no competing financial interests.

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Luscombe, N., Madan Babu, M., Yu, H. et al. Genomic analysis of regulatory network dynamics reveals large topological changes.Nature 431, 308–312 (2004). https://doi.org/10.1038/nature02782

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