Nonequilibrium model of short-range repression in gene transcription regulation

F. E. Garbuzov and V. V. Gursky
Phys. Rev. E 104, 014407 – Published 19 July 2021
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Abstract

Transcription factors are proteins that regulate gene activity by activating or repressing gene transcription. A special class of transcriptional repressors operates via a short-range mechanism, making local DNA regions inaccessible to binding by activators, and thus providing an indirect repressive action on the target gene. This mechanism is commonly modeled assuming that repressors interact with DNA under thermodynamic equilibrium and neglecting some configurations of the gene regulatory region. We elaborate on a more general nonequilibrium model of short-range repression using the graph formalism for transitions between gene states, and we apply analytical calculations to compare it with the equilibrium model in terms of the repression strength and expression noise. In contrast to the equilibrium approach, the new model allows us to separate two basic mechanisms of short-range repression. The first mechanism is associated with the recruiting of factors that mediate chromatin condensation, and the second one concerns the blocking of factors that mediate chromatin loosening. The nonequilibrium model demonstrates better performance on previously published gene expression data obtained for transcription factors controlling Drosophila development, and furthermore it predicts that the first repression mechanism is the most favorable in this system. The presented approach can be scaled to larger gene networks and can be used to infer specific modes and parameters of transcriptional regulation from gene expression data.

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  • Received 10 November 2020
  • Revised 21 April 2021
  • Accepted 24 June 2021

DOI:https://doi.org/10.1103/PhysRevE.104.014407

©2021 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
  1. Physical Systems
Physics of Living Systems

Authors & Affiliations

F. E. Garbuzov and V. V. Gursky*

  • Ioffe Institute, 26 Polytekhnicheskaya, St. Petersburg 194021, Russia

  • *gursky@math.ioffe.ru

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Issue

Vol. 104, Iss. 1 — July 2021

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