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Transient hysteresis and inherent stochasticity in gene regulatory networks

Author

Listed:
  • M. Pájaro

    (IIM-CSIC. Spanish National Research Council)

  • I. Otero-Muras

    (IIM-CSIC. Spanish National Research Council)

  • C. Vázquez

    (University of A Coruña)

  • A. A. Alonso

    (IIM-CSIC. Spanish National Research Council)

Abstract

Cell fate determination, the process through which cells commit to differentiated states is commonly mediated by gene regulatory motifs with mutually exclusive expression states. The classical deterministic picture for cell fate determination includes bistability and hysteresis, which enables the persistence of the acquired cellular state after withdrawal of the stimulus, ensuring a robust cellular response. However, stochasticity inherent to gene expression dynamics is not compatible with hysteresis, since the stationary solution of the governing Chemical Master Equation does not depend on the initial conditions. We provide a quantitative description of a transient hysteresis phenomenon reconciling experimental evidence of hysteretic behaviour in gene regulatory networks with inherent stochasticity: under sufficiently slow dynamics hysteresis is transient. We quantify this with an estimate of the convergence rate to the equilibrium and introduce a natural landscape capturing system’s evolution that, unlike traditional cell fate potential landscapes, is compatible with coexistence at the microscopic level.

Suggested Citation

  • M. Pájaro & I. Otero-Muras & C. Vázquez & A. A. Alonso, 2019. "Transient hysteresis and inherent stochasticity in gene regulatory networks," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
  • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-12344-w
    DOI: 10.1038/s41467-019-12344-w
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    Cited by:

    1. Pájaro, Manuel & Fajar, Noelia M. & Alonso, Antonio A. & Otero-Muras, Irene, 2022. "Stochastic SIR model predicts the evolution of COVID-19 epidemics from public health and wastewater data in small and medium-sized municipalities: A one year study," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

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