Computation of mRNA Number Distributions in Interactive Pathway Stochastic Gene Transcription Model

Abstract

Gene expression is a stochastic process characterized by fluctuations in the amount of mRNA in individual cells of an isogenic cell population. The fluctuation can be characterized by the mRNA number distribution Pm (t) , which denotes the probability of producing m copies of mRNA molecules in one cell at time t. For a given stochastic gene transcription model, how to solve the corresponding Pm (t) exact expression has been a hot research topic in this field. In the existing work, most of the results are solved for Pm (t) in the steady state case or in a specific parameter region, which affects us to fully understand the kinetic effects of different stochastic gene regulation patterns on the distribution of mRNA quantities. In this thesis, we explore the computation of Pm (t) for the cross-talk pathway model and give its exact expression under arbitrary system parameter conditions. The interactive signaling pathway model is successfully applied to elaborate stochastic transcription data of inducible genes in response to environmental changes. This work provides a kinetic theoretical basis for us to further investigate the interactive signaling pathway regulatory mechanism of gene transcription.