Influence of Complex Promoter Structure on Gene Expression

Abstract

A gene is often regulated by a variety of transcription factors, leading to complex promoter structure. However, how this structure affects gene expression remains elusive. Here, this paper studies a stochastic gene model with the promoter containing arbitrarily many active and inactive states. First, the authors use the binomial moment method to derive analytical steady-state distributions of the mRNA and protein numbers. Then, the authors analytically investigate how the promoter structure impacts the mean expression levels and the expression noise. Third, numerical simulation finds interesting phenomena, e.g., the common on-off model overestimates the expression noise in contrast to multiple-state models; the multi-on mechanism can reduce the expression noise more than the multi-off mechanism if the mean expression level is kept the same; and multiple exits of transcription can result in multimodal distributions.