Dynamic behavior of stochastic gene expression models in the presence of bursting

TL;DR

This paper analyzes stochastic gene expression models with bursting, providing general results applicable to various distributions and expression patterns, supported by examples including geometric and exponential burst sizes.

Contribution

It offers a comprehensive analysis of gene expression models with bursting, covering general distributions and both inducible and repressible patterns, with practical examples.

Findings

Results applicable to geometric and exponential burst size distributions

Models applicable to both prokaryotic and eukaryotic gene expression

Provides analytical insights into stochastic gene expression dynamics

Abstract

This paper considers the behavior of discrete and continuous mathematical models for gene expression in the presence of transcriptional/translational bursting. We treat this problem in generality with respect to the distribution of the burst size as well as the frequency of bursting, and our results are applicable to both inducible and repressible expression patterns in prokaryotes and eukaryotes. We have given numerous examples of the applicability of our results, especially in the experimentally observed situation that burst size is geometrically or exponentially distributed.