Integrated analysis of motif activity and gene expression changes of transcription factors

  1. Susanne Mandrup1
  1. 1Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense, Denmark;
  2. 2Research and Development, Beiersdorf AG, 20245 Hamburg, Germany
  1. 3 These authors contributed equally to this work.

  • 4 Present address: Institute for Diabetes and Cancer, Helmholtz Center Munich, German Research Center for Environmental Health, 85764 Neuherberg, Germany

  • Corresponding author: s.mandrup{at}bmb.sdu.dk
  • Abstract

    The ability to predict transcription factors based on sequence information in regulatory elements is a key step in systems-level investigation of transcriptional regulation. Here, we have developed a novel tool, IMAGE, for precise prediction of causal transcription factors based on transcriptome profiling and genome-wide maps of enhancer activity. High precision is obtained by combining a near-complete database of position weight matrices (PWMs), generated by compiling public databases and systematic prediction of PWMs for uncharacterized transcription factors, with a state-of-the-art method for PWM scoring and a novel machine learning strategy, based on both enhancers and promoters, to predict the contribution of motifs to transcriptional activity. We applied IMAGE to published data obtained during 3T3-L1 adipocyte differentiation and showed that IMAGE predicts causal transcriptional regulators of this process with higher confidence than existing methods. Furthermore, we generated genome-wide maps of enhancer activity and transcripts during human mesenchymal stem cell commitment and adipocyte differentiation and used IMAGE to identify positive and negative transcriptional regulators of this process. Collectively, our results demonstrate that IMAGE is a powerful and precise method for prediction of regulators of gene expression.

    Footnotes

    • Received July 6, 2017.
    • Accepted December 1, 2017.

    This article is distributed exclusively by Cold Spring Harbor Laboratory Press for the first six months after the full-issue publication date (see http://genome.cshlp.org/site/misc/terms.xhtml). After six months, it is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.

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