Analytical results for a generalized model of bursty gene expression with molecular memory

Huahai Qiu, Bengong Zhang, and Tianshou Zhou
Phys. Rev. E 100, 012128 – Published 19 July 2019

Abstract

The activation of a gene is a complex biochemical process and could involve small steps, creating a memory between individual events. However, the effect of this molecular memory was often neglected in previous work. How the molecular memory affects gene expression remains not fully explored. We analyze a stochastic model of bursty gene expression, where the waiting time from inactivation to activation is assumed to follow a nonexponential (in fact, Erlang) distribution. We derive the analytical expression for the gene-product distribution, which explicitly traces the effect of molecule memory. Interestingly, we find that the effect of molecular memory is equivalent to the introduction of feedback. In addition, we analytically show that the stationary distribution is always super-Poissonian, independent of the detail of the waiting-time distribution, and there is the optimal step size that minimizes the Fano factor for any given mean burst size and is a decreasing function of the mean burst size. These analytical results indicate that molecular memory is an unneglectable factor affecting gene expression.

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  • Received 3 March 2019
  • Revised 30 April 2019

DOI:https://doi.org/10.1103/PhysRevE.100.012128

©2019 American Physical Society

Physics Subject Headings (PhySH)

Physics of Living SystemsStatistical Physics & Thermodynamics

Authors & Affiliations

Huahai Qiu1, Bengong Zhang1, and Tianshou Zhou1,2,*

  • 1School of Mathematics and Computers, Wuhan Textile University, Wuhan 430200, People's Republic of China
  • 2Key Laboratory of Computational Mathematics, Guangdong Province, and School of Mathematics, Sun Yat-sen University, Guangzhou 510275, People's Republic of China

  • *Corresponding author: mcszhtsh@mail.sysu.edu.cn

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Vol. 100, Iss. 1 — July 2019

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