Post-transcriptional regulation of noise in protein distributions during gene expression

Abstract

The intrinsic stochasticity of gene expression can lead to large variability of protein levels across a population of cells. Variability (or noise) in protein distributions can be modulated by cellular mechanisms of gene regulation; in particular, there is considerable interest in understanding the role of post-transcriptional regulation. To address this issue, we propose and analyze a stochastic model for post-transcriptional regulation of gene expression. The analytical solution of the model provides insight into the effects of different mechanisms of post-transcriptional regulation on the noise in protein distributions. The results obtained also demonstrate how different sources of intrinsic noise in gene expression can be discriminated based on observations of regulated protein distributions.

arXiv commentAccepted by Physical Review Letters

References in corpus (3)

• Analytical distributions for stochastic gene expression
• Graded and Binary Responses in Stochastic Gene Expression
• Efficient Degradation and Expression Prioritization with Small RNAs

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• Stochastic single-gene auto-regulation
• Stabilizing Gene Regulatory Networks Through Feedforward Loops
• Stochastic gene expression conditioned on large deviations
• Quantification of noise in the bifunctionality-induced post-translational modification
• Quantifying the noise in bursty gene expression under regulation by small RNAs