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Combinatorial binding predicts spatio-temporal cis-regulatory activity

Author

Listed:
  • Robert P. Zinzen

    (European Molecular Biology Laboratory)

  • Charles Girardot

    (European Molecular Biology Laboratory)

  • Julien Gagneur

    (European Molecular Biology Laboratory)

  • Martina Braun

    (European Molecular Biology Laboratory)

  • Eileen E. M. Furlong

    (European Molecular Biology Laboratory)

Abstract

Development requires the establishment of precise patterns of gene expression, which are primarily controlled by transcription factors binding to cis-regulatory modules. Although transcription factor occupancy can now be identified at genome-wide scales, decoding this regulatory landscape remains a daunting challenge. Here we used a novel approach to predict spatio-temporal cis-regulatory activity based only on in vivo transcription factor binding and enhancer activity data. We generated a high-resolution atlas of cis-regulatory modules describing their temporal and combinatorial occupancy during Drosophila mesoderm development. The binding profiles of cis-regulatory modules with characterized expression were used to train support vector machines to predict five spatio-temporal expression patterns. In vivo transgenic reporter assays demonstrate the high accuracy of these predictions and reveal an unanticipated plasticity in transcription factor binding leading to similar expression. This data-driven approach does not require previous knowledge of transcription factor sequence affinity, function or expression, making it widely applicable.

Suggested Citation

  • Robert P. Zinzen & Charles Girardot & Julien Gagneur & Martina Braun & Eileen E. M. Furlong, 2009. "Combinatorial binding predicts spatio-temporal cis-regulatory activity," Nature, Nature, vol. 462(7269), pages 65-70, November.
  • Handle: RePEc:nat:nature:v:462:y:2009:i:7269:d:10.1038_nature08531
    DOI: 10.1038/nature08531
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    Cited by:

    1. M S Vijayabaskar & Debbie K Goode & Nadine Obier & Monika Lichtinger & Amber M L Emmett & Fatin N Zainul Abidin & Nisar Shar & Rebecca Hannah & Salam A Assi & Michael Lie-A-Ling & Berthold Gottgens & , 2019. "Identification of gene specific cis-regulatory elements during differentiation of mouse embryonic stem cells: An integrative approach using high-throughput datasets," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-29, November.
    2. Andrew Gordon Wilson & David A. Knowles & Zoubin Ghahramani, 2011. "Gaussian Process Regression Networks," Papers 1110.4411, arXiv.org.

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