Regulation of transcription reactivation dynamics exiting mitosis

PLoS Comput Biol. 2021 Oct 4;17(10):e1009354. doi: 10.1371/journal.pcbi.1009354. eCollection 2021 Oct.

Abstract

Proliferating cells experience a global reduction of transcription during mitosis, yet their cell identity is maintained and regulatory information is propagated from mother to daughter cells. Mitotic bookmarking by transcription factors has been proposed as a potential mechanism to ensure the reactivation of transcription at the proper set of genes exiting mitosis. Recently, mitotic transcription and waves of transcription reactivation have been observed in synchronized populations of human hepatoma cells. However, the study did not consider that mitotic-arrested cell populations progressively desynchronize leading to measurements of gene expression on a mixture of cells at different internal cell-cycle times. Moreover, it is not well understood yet what is the precise role of mitotic bookmarking on mitotic transcription as well as on the transcription reactivation waves. Ultimately, the core gene regulatory network driving the precise transcription reactivation dynamics remains to be identified. To address these questions, we developed a mathematical model to correct for the progressive desynchronization of cells and estimate gene expression dynamics with respect to a cell-cycle pseudotime. Furthermore, we used a multiple linear regression model to infer transcription factor activity dynamics. Our analysis allows us to characterize waves of transcription factor activities exiting mitosis and predict a core gene regulatory network responsible of the transcription reactivation dynamics. Moreover, we identified more than 60 transcription factors that are highly active during mitosis and represent new candidates of mitotic bookmarking factors which could be relevant therapeutic targets to control cell proliferation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Line, Tumor
  • Cell Proliferation / genetics
  • Computational Biology / methods*
  • Gene Expression Regulation / genetics
  • Humans
  • Mitosis / genetics*
  • Transcription Factors / genetics
  • Transcription Factors / metabolism
  • Transcription, Genetic / genetics*
  • Transcriptome / genetics

Substances

  • Transcription Factors

Grants and funding

This work was possible thanks to funding from the LabEx INRT grant (ANR-10-LABX-0030-INRT, a French State fund managed by the Agence Nationale de la Recherche under the frame program Investissements d’Avenir ANR-10-IDEX-0002-02), and the IDEX attractivité program of the University of Strasbourg (IDEX2017) both obtained by NM. SS’s salary was cover with LabEx INRT founds and AR’s salary with IDEX founds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.