Effect of transcription factor resource sharing on gene expression noise

Das, Debapratim; Dey, Supravat; Brewster, Robert C.; Choubey, Sandeep

doi:10.1371/journal.pcbi.1005491

Cited by 46 publications

(30 citation statements)

References 101 publications

(94 reference statements)

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“…An important contributor to transcriptional noise is fluctuations in chromatin accessibility (Brown et al, 2013) and the limiting numbers of transcription factors. Single-cell chromatin accessibility measurements support the link between accessibility and transcriptional heterogeneity (Buenrostro et al, 2015), while mathematical modelling of the competition between genes for transcription factors revealed that this competition is sufficient to enhance mRNA copy number variability within an isogenic population (Das et al, 2017). Furthermore, pausing of RNA polymerase, a critical step during the initiation of transcription (Adelman and Lis, 2012) contributes to the stochasticity of gene expression.…”

Section: Sources Of Transcriptional Variabilitymentioning

confidence: 92%

Ageing and sources of transcriptional heterogeneity

Nikopoulou

Tessarz

2019

Biological Chemistry

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Cellular heterogeneity is an important contributor to biological function and is employed by cells, tissues and organisms to adapt, compensate, respond, defend and/or regulate specific processes. Research over the last decades has revealed that transcriptional noise is a major driver for cell-to-cell variability. In this review we will discuss sources of transcriptional variability, in particular bursting of gene expression and how it could contribute to cellular states and fate decisions. We will highlight recent developments in single cell sequencing technologies that make it possible to address cellular heterogeneity in unprecedented detail. Finally, we will review recent literature, in which these new technologies are harnessed to address pressing questions in the field of ageing research, such as transcriptional noise and cellular heterogeneity in the course of ageing.

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Section: Sources Of Transcriptional Variabilitymentioning

confidence: 92%

Ageing and sources of transcriptional heterogeneity

Nikopoulou

Tessarz

2019

Biological Chemistry

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“…Binding competition can generate noise in two possible ways. First, TF binding is a dynamic process consisting of rapid binding and unbinding steps (Burger et al, 2010;Das et al, 2017). Thus, competition between TFs leads to a scenario where a gene is regulated by different subsets of TFs at different points of time, thus generating temporal variation in TF binding (Fig.…”

Section: Overlaps In Tf Binding Sites Lead To Higher Noisementioning

confidence: 99%

Transcription factor binding process is the primary driver of noise in gene expression

Parab

Pal

Dhar

2020

Preprint

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SummaryCellular processes driven by coordinated actions of individual genes generate cellular phenotypes. Stochastic variations in these processes lead to phenotypic heterogeneity that often has important implications for antibiotic persistence, mutation penetrance, cancer growth and anti-cancer drug resistance. However, the architecture of noise in cellular processes has remained largely unexplored even though expression noise in individual genes have been widely studied. Here we quantify noise in biological processes in yeast and through an integrated quantitative model show that the number of regulating transcription factors and their binding dynamics are the primary drivers of noise. Specifically, binding dynamics arising from competition and cooperation among TFs for promoter binding can predict a large fraction of noise variation. Our work reveals a novel mechanism of noise regulation that arises out of the dynamic nature of gene regulation and is not dependent on specific transcription factor or specific promoter sequence.

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“…There is a history of using kinetic models to describe the dynamic processes of transcriptional regulation [19,20] In particular these models have been used to inform how the mean transcriptional levels and the variability around that mean depends on the dynamics of the processes that regulate transcription. This has culminated in a prevalent "On-off" model [14,19,[21][22][23][24][25][26][27][28] of promoter dynamics that considers initiation as being regulated by switching between a transcriptionally active and inactive state, the origin of this switching has been proposed as related to mechanisms such as transcription factor dynamics, chromatin accessibility or condensates of transcriptional machinery. This model has been extended to include the dynamics of the elongation process, to varying degrees; the roles of simple stochastic hopping, pausing and steric hindrance have all been considered and their contribution to phenomena such as traffic jams and transcription rate has been examined.…”

Section: Introductionmentioning

confidence: 99%

Probing mechanisms of transcription elongation through cell-to-cell variability of RNA polymerase

Ali

Choubey

Das

et al. 2019

Preprint

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The process of transcription initiation and elongation are primary points of control in the regulation of gene expression. While biochemical studies have uncovered the mechanisms involved in controlling transcription at each step, how these mechanisms manifest in vivo at the level of individual genes is still unclear. Recent experimental advances have enabled single-cell measurements of RNAP molecules engaged in the process of transcribing a gene of interest. In this manuscript, we use Gillespie simulations to show that measurements of cellto-cell variability of RNAP numbers and inter-polymerase distances can reveal the prevailing mode of regulation of a given gene. Mechanisms of regulation at each step, from initiation to elongation dynamics, produce qualitatively distinct signatures which can further be used to discern between them. Intriguingly, depending on the initiation kinetics, stochastic elongation can either enhance or suppress cell-to-cell variability at the RNAP level. To demonstrate the value of this framework, we analyze RNAP number distribution data for ribosomal genes in S. cerevisiae from three previously published studies and show that this approach provides crucial mechanistic insights into the transcriptional regulation of these genes. Author SummaryThe process of transcription comprises many distinct steps and understanding the regulation of each of these steps provides insight into how the levels of gene expression are controlled in the cell. In this manuscript, we use stochastic simulations to explore how regulation at the level of elongation and initiation together influences the distribution of actively transcribing RNAP on a gene. We find that each of these steps of regulation leaves a distinct imprint on the gene-to-gene variability of number of actively transcribing RNAP on the gene and their inter-RNAP distances. Using these results, we analyze recent experimental data of transcribing RNAP distributions and find that the perturbations in these studies primarily impact the transcription initiation dynamics of the genes.

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Effect of transcription factor resource sharing on gene expression noise

Cited by 46 publications

References 101 publications

Ageing and sources of transcriptional heterogeneity

Ageing and sources of transcriptional heterogeneity

Transcription factor binding process is the primary driver of noise in gene expression

Probing mechanisms of transcription elongation through cell-to-cell variability of RNA polymerase

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