1. Computational and Systems Biology
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Inference of gene regulation functions from dynamic transcriptome data

  1. Patrick Hillenbrand
  2. Kerstin C Maier
  3. Patrick Cramer
  4. Ulrich Gerland  Is a corresponding author
  1. Technical University of Munich, Germany
  2. Max-Planck Institute for Biophysical Chemistry, Germany
  3. Max Planck Institute for Biophysical Chemistry, Germany
Research Article
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Cite this article as: eLife 2016;5:e12188 doi: 10.7554/eLife.12188

Abstract

To quantify gene regulation, a function is required that relates transcription factor binding to DNA (input) to the rate of mRNA synthesis from a target gene (output). Such a 'gene regulation function' (GRF) generally cannot be measured because the experimental titration of inputs and simultaneous readout of outputs is difficult. Here we show that GRFs may instead be inferred from natural changes in cellular gene expression, as exemplified for the cell cycle in the yeast S. cerevisiae. We develop this inference approach based on a time series of mRNA synthesis rates from a synchronized population of cells observed over three cell cycles. We first estimate the functional form of how input transcription factors determine mRNA output and then derive GRFs for target genes in the clb2 gene cluster that are expressed during G2/M phase. Systematic analysis of additional GRFs suggests a network architecture that rationalizes transcriptional cell cycle oscillations. We find that a transcription factor network alone can produce oscillations in mRNA expression, but that additional input from cyclin oscillations is required to arrive at the native behaviour of the cell cycle oscillator.

Data availability

The following previously published data sets were used

Article and author information

Author details

  1. Patrick Hillenbrand

    Department of Physics, Technical University of Munich, Garching, Germany
    Competing interests
    No competing interests declared.
  2. Kerstin C Maier

    Department of Molecular Biology, Max-Planck Institute for Biophysical Chemistry, Göttingen, Germany
    Competing interests
    No competing interests declared.
  3. Patrick Cramer

    Department of Molecular Biology, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany
    Competing interests
    Patrick Cramer, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5454-7755
  4. Ulrich Gerland

    Department of Physics, Technical University of Munich, Garching, Germany
    For correspondence
    gerland@tum.de
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0859-6422

Funding

Deutsche Forschungsgemeinschaft

  • Patrick Cramer
  • Ulrich Gerland

Volkswagen Foundation

  • Patrick Cramer

Bayerisches Staatsministerium für Bildung und Kultus, Wissenschaft und Kunst

  • Ulrich Gerland

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

Reviewing Editor

  1. Sarah A Teichmann, EMBL-European Bioinformatics Institute & Wellcome Trust Sanger Institute, United Kingdom

Publication history

  1. Received: October 9, 2015
  2. Accepted: September 20, 2016
  3. Accepted Manuscript published: September 21, 2016 (version 1)
  4. Version of Record published: October 20, 2016 (version 2)

Copyright

© 2016, Hillenbrand 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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