Noise tunability in a gene model with star-type promoter structure

Abstract

Expression noise is identified as a main source of cell-to-cell variability, whereas a gene’s promoter structure giving rise to noisy expression may be complex, in particular in eukaryotic cells. Here, we analyze a biologically reasonable gene model at the transcription level, where the promoter appears in a star-type structure, i.e. reversible transitions exist only between active and inactive states of the promoter and there are no links between the inactive states. We first derive the analytical steady-state mRNA distribution governed by a master equation, which provides the complete information on stochastic behavior of the underlying system. Interestingly, we find that the more the branch number (i.e. the number of inactive states) is, the larger is the skewness of the mRNA distribution. Then, we show that the mRNA noise defined as the ratio of the standard difference over the mean can arrive at the minimal value, independent of the branch number. Meanwhile, the noise can also arrive at the maximal value that increases with the branch number. These results provide insight into how a multi-off mechanism controls the mRNA expression and further cell-to-cell variability at the expression level.

Keywords:

• Gene model
• probability distribution
• skewness
• expression noise
• chemical master equation

AMS Subject Classifications:

• 92C37
• 92C40
• 92C45

Notes

No potential conflict of interest was reported by the authors.