On a stochastic gene expression with pre-mRNA, mRNA and protein contribution

TL;DR

This paper models stochastic gene expression including pre-mRNA, mRNA, and protein, analyzing long-term behavior and revealing new dynamics like limit cycles not seen in simpler models.

Contribution

It introduces a stochastic gene expression model with pre-mRNA, extending previous models, and analyzes its long-term behavior including bistability and limit cycles.

Findings

Identification of long-term behavior as a piece-wise deterministic Markov process

Discovery of limit cycle behavior in the deterministic limit

Numerical validation of distributional properties

Abstract

In this paper we develop a model of stochastic gene expression, which is an extension of the model investigated in the paper [T. Lipniacki, P. Paszek, A. Marciniak-Czochra, A.R. Brasier, M. Kimmel, Transcriptional stochasticity in gene expression, J. Theor. Biol. 238 (2006) 348-367]. In our model, stochastic effects still originate from random uctuations in gene activity status, but we precede mRNA production by the formation of pre-mRNA, which enriches classical transcription phase. We obtain a stochastically regulated system of ordinary differential equations (ODEs) describing evolution of pre-mRNA, mRNA and protein levels. We perform mathematical analysis of a long-time behaviour of this stochastic process, identified as a piece-wise deterministic Markov process (PDMP). We check exact results using numerical simulations for the distributions of all three types of particles. Moreover, we investigate the deterministic (adiabatic) limit state of the process, when depending on parameters it can exhibit two specific types of behavior: bistability and the existence of the limit cycle. The latter one is not present when only two kinds of gene expression products are considered.