Multiple stochastic point processes in gene expression

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Abstract

We generalize the idea of multiple-stochasticity in chemical reaction systems to gene expression. Using Chemical Langevin Equation approach we investigate how this multiple-stochasticity can influence the overall molecular number fluctuations. We show that the main sources of this multiple- stochasticity in gene expression could be the randomness in transcription and translation initiation times which in turn originates from the underlying bio-macromolecular recognition processes such as the site-specific DNA-protein interactions and therefore can be internally regulated by the supra-molecular structural factors such as the condensation/super-coiling of DNA. Our theory predicts that (1) in case of gene expression system, the variances (φ) introduced by the randomness in transcription and translation initiation-times approximately scales with the degree of condensation (s) of DNA or mRNA as φ α s -6. From the theoretical analysis of the Fano factor as well as coefficient of variation associated with the protein number fluctuations we predict that (2) unlike the singly-stochastic case where the Fano factor has been shown to be a monotonous function of translation rate, in case of multiple-stochastic gene expression the Fano factor is a turn over function with a definite minimum. This in turn suggests that the multiple-stochastic processes can also be well tuned to behave like a singly-stochastic point processes by adjusting the rate parameters. © 2008 Springer Science+Business Media, LLC.

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APA

Murugan, R. (2008). Multiple stochastic point processes in gene expression. Journal of Statistical Physics, 131(1), 153–165. https://doi.org/10.1007/s10955-008-9484-4

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