A continuum model of transcriptional bursting

Corrigan, Adam; Tunnacliffe, Edward; Cannon, Danielle; Chubb, Jonathan R.

doi:10.7554/elife.13051

Cited by 180 publications

(208 citation statements)

References 50 publications

Supporting

Mentioning

192

Contrasting

Order By: Relevance

“…on, off-repressed, and off- poised; Bintu et al, 2016; Chavali et al, 2015) and even a continuum of states (Corrigan et al, 2016) have been proposed. Still, the two-state model is useful because of the clear mathematical relationships between the model parameters of burst frequency and burst size and the moments of an expected distribution of transcript numbers, which are mathematically related to distribution noise (Skupsky et al, 2010).…”

Section: Figurementioning

confidence: 99%

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise

et al. 2018

View full text Add to dashboard Cite

SUMMARY Noisy gene expression generates diverse phenotypes, but little is known about mechanisms that modulate noise. Combining experiments and modeling, we studied how tumor necrosis factor (TNF) initiates noisy expression of latent HIV via the transcription factor nuclear factor κB (NF-κB) and how the HIV genomic integration site modulates noise to generate divergent (low-versus-high) phenotypes of viral activation. We show that TNF-induced transcriptional noise varies more than mean transcript number and that amplification of this noise explains low-versus-high viral activation. For a given integration site, live-cell imaging shows that NF-κB activation correlates with viral activation, but across integration sites, NF-κB activation cannot account for differences in transcriptional noise and phenotypes. Instead, differences in transcriptional noise are associated with differences in chromatin state and RNA polymerase II regulation. We conclude that, whereas NF-κB regulates transcript abundance in each cell, the chromatin environment modulates noise in the population to support diverse HIV activation in response to TNF.

show abstract

Section: Figurementioning

confidence: 99%

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise

et al. 2018

View full text Add to dashboard Cite

show abstract

“…This variation is thought to arise, at least in part, from uncoordinated bursts of transcription. Visualization of living yeast, Dictyostelium and cultured mammalian cells provides further support for sporadic and uncoordinated bursts across cell populations (Yunger et al, 2010; Larson et al, 2011; Suter et al, 2011; Corrigan et al, 2016). …”

Section: Introductionmentioning

confidence: 96%

Enhancer Control of Transcriptional Bursting

Fukaya

Lim

Levine

2016

Cell

645

631

View full text Add to dashboard Cite

Summary Transcription is episodic, consisting of a series of discontinuous bursts. Using live imaging methods and quantitative analysis, we examine transcriptional bursting in living Drosophila embryos. Different developmental enhancers positioned downstream of synthetic reporter genes produce transcriptional bursts with similar amplitudes and duration, but generate very different bursting frequencies, with strong enhancers producing more bursts than weak enhancers. Insertion of an insulator reduces the number of bursts and the corresponding level of gene expression, suggesting that enhancer regulation of bursting frequency is a key parameter of gene control in development. We also show that linked reporter genes exhibit coordinated bursting profiles when regulated by a shared enhancer, challenging conventional models of enhancer-promoter looping.

show abstract

“…We reached this conclusion by showing that only burst size modulation can explain the experimentally observed changes in mean pulse amplitude and pulse amplitude distribution with increasing energy stress level. It should be noted that although our results provide clear evidence in favor of phosphatase burst-size modulation, direct confirmation of this mechanism necessitates the use of single-molecule techniques such as RNA-FISH [44,45] that can be used to estimate stochastic properties of gene expression. This result raises the question whether pulsatile σ B response can achieve proportional expression of downstream genes, as was previously suggested [13,46].…”

Section: Resultsmentioning

confidence: 81%

Role of Autoregulation and Relative Synthesis of Operon Partners in Alternative Sigma Factor Networks

2016

View full text Add to dashboard Cite

Despite the central role of alternative sigma factors in bacterial stress response and virulence their regulation remains incompletely understood. Here we investigate one of the best-studied examples of alternative sigma factors: the σB network that controls the general stress response of Bacillus subtilis to uncover widely relevant general design principles that describe the structure-function relationship of alternative sigma factor regulatory networks. We show that the relative stoichiometry of the synthesis rates of σB, its anti-sigma factor RsbW and the anti-anti-sigma factor RsbV plays a critical role in shaping the network behavior by forcing the σB network to function as an ultrasensitive negative feedback loop. We further demonstrate how this negative feedback regulation insulates alternative sigma factor activity from competition with the housekeeping sigma factor for RNA polymerase and allows multiple stress sigma factors to function simultaneously with little competitive interference.

show abstract

A continuum model of transcriptional bursting

Cited by 180 publications

References 50 publications

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise

NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise

Enhancer Control of Transcriptional Bursting

Role of Autoregulation and Relative Synthesis of Operon Partners in Alternative Sigma Factor Networks

Contact Info

Product

Resources

About