Effect of transcription reinitiation in stochastic gene expression
Rajesh Karmakar, Amit Kumar Das

TL;DR
This paper investigates how transcription reinitiation affects stochastic gene expression, revealing that it can variably influence mRNA mean and variability depending on the gene network model.
Contribution
It demonstrates that RNAP-II based reinitiation can have diverse effects on mRNA levels and variability, and proposes a new perspective on feedback mechanisms in gene regulation.
Findings
Reinitiation decreases mRNA mean and Fano factor in constitutive networks.
Reinitiation can increase or decrease mRNA mean and variability in other network types.
Constitutive networks with reinitiation act like negative feedback circuits.
Abstract
Gene expression (GE) is an inherently random or stochastic or noisy process. The randomness in different steps of GE, e.g., transcription, translation, degradation, etc., leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans. Stochastic gene expression has important consequences for cellular function. The random fluctuations in protein levels produce variability in cellular behavior. It is beneficial in some contexts and harmful to others. These situations include stress response, metabolism, development, cell cycle, circadian rhythms, and aging. Different model studies e.g., constitutive, two-state, etc., reveal that the fluctuations in mRNA and protein levels arise from different steps of gene expression among which the steps in transcription have the maximum effect. The pulsatile mRNA production through…
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