Gene expression dynamics with stochastic bursts: exact results for a coarse-grained model

Abstract

We present a theoretical framework to analyze the dynamics of gene expression with stochastic bursts. Beginning with an individual-based model which fully accounts for the messenger RNA (mRNA) and protein populations, we propose a novel expansion of the master equation for the joint process. The resulting coarse-grained model reduces the dimensionality of the system, describing only the protein population while fully accounting for the effects of discrete and fluctuating mRNA population. Closed form expressions for the stationary distribution of the protein population and mean first-passage times of the coarse-grained model are derived and large-scale Monte Carlo simulations show that the analysis accurately describes the individual-based process accounting for mRNA population, in contrast to the failure of commonly proposed diffusion-type models.

5 pages, 4 figures

References in corpus (3)

• Analytical distributions for stochastic gene expression
• Exact distributions for stochastic gene expression models with bursting and feedback
• Bursting noise in gene expression dynamics: Linking microscopic and mesoscopic models

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