Dissecting the DNA binding landscape and gene regulatory network of p63 and p53

  1. Konstantin Riege
  2. Helene Kretzmer
  3. Arne Sahm
  4. Simon S McDade
  5. Steve Hoffmann
  6. Martin Fischer  Is a corresponding author
  1. Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Germany
  2. Max Planck Institute for Molecular Genetics, Germany
  3. Queen's University Belfast, United Kingdom

Abstract

The transcription factor p53 is the best-known tumor suppressor, but its sibling p63 is a master regulator of epidermis development and a key oncogenic driver in squamous cell carcinomas (SCC). Despite multiple gene expression studies becoming available, the limited overlap of reported p63-dependent genes has made it difficult to decipher the p63 gene regulatory network. Particularly, analyses of p63 response elements differed substantially among the studies. To address this intricate data situation, we provide an integrated resource that enables assessing the p63-dependent regulation of any human gene of interest. We use a novel iterative de novo motif search approach in conjunction with extensive ChIP-seq data to achieve a precise global distinction between p53 and p63 binding sites, recognition motifs, and potential co-factors. We integrate these data with enhancer:gene associations to predict p63 target genes and identify those that are commonly de-regulated in SCC representing candidates for prognosis and therapeutic interventions.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

The following previously published data sets were used

Article and author information

Author details

  1. Konstantin Riege

    Computational Biology, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Helene Kretzmer

    Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Arne Sahm

    Computational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7330-1790
  4. Simon S McDade

    Queen's University Belfast, Belfast, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  5. Steve Hoffmann

    Computational Biology Group, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Martin Fischer

    Computational Biology, Leibniz Institute on Aging - Fritz Lipmann Institute (FLI), Jena, Germany
    For correspondence
    Martin.Fischer@leibniz-fli.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3429-1876

Funding

Deutsche Forschungsgemeinschaft (FI 1993/2-1)

  • Martin Fischer

Bundesministerium für Bildung und Forschung (031L016D)

  • Steve Hoffmann

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Ashish Lal, National Institutes of Health, United States

Version history

  1. Received: September 21, 2020
  2. Accepted: December 1, 2020
  3. Accepted Manuscript published: December 2, 2020 (version 1)
  4. Version of Record published: December 14, 2020 (version 2)

Copyright

© 2020, Riege et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Konstantin Riege
  2. Helene Kretzmer
  3. Arne Sahm
  4. Simon S McDade
  5. Steve Hoffmann
  6. Martin Fischer
(2020)
Dissecting the DNA binding landscape and gene regulatory network of p63 and p53
eLife 9:e63266.
https://doi.org/10.7554/eLife.63266

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https://doi.org/10.7554/eLife.63266

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