Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models

@article{Kumar2014TranscriptionalBI,
  title={Transcriptional Bursting in Gene Expression: Analytical Results for General Stochastic Models},
  author={Niraj Kumar and Abhyudai Singh and Rahul V. Kulkarni},
  journal={PLoS Computational Biology},
  year={2014},
  volume={11}
}
Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Such bursting has important consequences for cell-fate decisions in diverse processes ranging from HIV-1 viral infections to stem-cell differentiation. It is generally assumed that bursts are geometrically distributed and that they arrive according to a Poisson process. On the other hand, recent single-cell experiments provide evidence for complex burst arrival… 
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113 Citations
Background Citations
36
Methods Citations
9
Results Citations
1

113 Citations

Exact distributions for stochastic gene expression models with arbitrary promoter architecture and translational bursting.

A stochastic model of bursty gene expression is developed, which considers the complex promoter architecture governing the variability in mRNA expression and a general distribution characterizing translational burst, and derives the analytical expression for the corresponding protein steady-state distribution and all moment statistics of protein counts.

Effect of gene-expression bursts on stochastic timing of cellular events

The effect of burst size distribution is investigated by looking at how the feedback regulation strategy that minimizes noise in timing around a given time deviates from the strategy when the burst size is deterministic, and results show that the feedback strategy for deterministic burst case is quite robust to change in Burst size distribution.

Exact solution of stochastic gene expression models with bursting, cell cycle and replication dynamics.

It is shown that protein distributions are well approximated by the solution of implicit models (a negative binomial) when the mean number of mRNAs produced per cycle is low and the cell cycle length variability is large and when these conditions are not met, the distributions are either almost bimodal or else display very flat regions near the mode and cannot be described by implicit models.

Gene expression noise is affected differentially by feedback in burst frequency and burst size

A piecewise deterministic model for gene expression of a self-regulating gene is studied and results show that in the low noise regime, both feedbacks are similar in term of their noise buffering abilities.

Gene expression noise is affected differentially by feedback in burst frequency and burst size

A piecewise deterministic model for gene expression of a self-regulating gene is studied and results show that in the low noise regime, both feedbacks are similar in term of their noise buffering abilities.

Constraining the complexity of promoter dynamics using fluctuations in gene expression.

It is shown that measurements of mRNA fluctuations can be used to set fundamental bounds on the complexity of promoter dynamics, and analytical expressions are derived which connect the Fano factor of mRNA distributions to the waiting-time distribution for promoter switching between inactive and active states.

Macroscopic limits, analytical distributions, and noise structure for stochastic gene expression with coupled feedback loops

The theory unifies and generalizes the discrete and continuous gene expression models proposed previously by viewing the latter as various macroscopic limits of the former and results reveal a strong synergistic interaction between positive and negative feedback loops and a critical phase-transition-like phenomenon in the regime of slow promoter switching.

Modulation of stochastic gene expression by nuclear export processes

Inside mammalian cells, single genes are known to be transcribed in stochastic bursts leading to the synthesis of nuclear RNAs that are subsequently exported to the cytoplasm to create mRNAs. We…

Kinetic characteristics of transcriptional bursting in a complex gene model with cyclic promoter structure.

A general model of the promoter cycle consisting of multi-OFF states and multi-ON states is introduced, focusing on the effects ofMulti-ON mechanisms on transcriptional bursting kinetics, and results indicate that burst size follows a mixed geometric distribution rather than a single geometric distribution assumed in previous studies.

Inferring transcriptional bursting kinetics from single-cell snapshot data using a generalized telegraph model

An interpretable and tractable model is developed, the generalized telegraph model (GTM), to carve transcriptional bursting that allows arbitrary dwell-time distributions, rather than exponential distributions, to be incorporated into the ON and OFF switching process.
...

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