Transcriptional burst frequency and burst size are equally modulated across the human genome

Gladstone Institutes, San Francisco, CA 94158.
Proceedings of the National Academy of Sciences (Impact Factor: 9.81). 10/2012; 109(43):17454-9. DOI: 10.1073/pnas.1213530109
Source: PubMed

ABSTRACT Gene expression occurs either as an episodic process, characterized by pulsatile bursts, or as a constitutive process, characterized by a Poisson-like accumulation of gene products. It is not clear which mode of gene expression (constitutive versus bursty) predominates across a genome or how transcriptional dynamics are influenced by genomic position and promoter sequence. Here, we use time-lapse fluorescence microscopy to analyze 8,000 individual human genomic loci and find that at virtually all loci, episodic bursting-as opposed to constitutive expression-is the predominant mode of expression. Quantitative analysis of the expression dynamics at these 8,000 loci indicates that both the frequency and size of the transcriptional bursts varies equally across the human genome, independent of promoter sequence. Strikingly, weaker expression loci modulate burst frequency to increase activity, whereas stronger expression loci modulate burst size to increase activity. Transcriptional activators such as trichostatin A (TSA) and tumor necrosis factor α (TNF) only modulate burst size and frequency along a constrained trend line governed by the promoter. In summary, transcriptional bursting dominates across the human genome, both burst frequency and burst size vary by chromosomal location, and transcriptional activators alter burst frequency and burst size, depending on the expression level of the locus.

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Available from: Mike Simpson, Jun 30, 2014
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    • "Recent assays in single cells confirmed transcriptional bursting in many organisms (Golding et al, 2005; Chubb et al, 2006; Raj et al, 2006; Zenklusen et al, 2008). Although not all genes are transcribed in bursts (Zenklusen et al, 2008), bursting appears predominant in mammals (Suter et al, 2011; Dar et al, 2012; Bahar Halpern et al, 2015). The mechanisms causing bursts in eukaryotes are still elusive but most likely involve the interplay between transcription factors (Larson et al, 2013; Senecal et al, 2014), chromatin remodelers (Coulon et al, 2013; Voss & Hager, 2013), the formation of gene loops and pre-initiation complexes (Blake et al, 2003; Zenklusen et al, 2008), and transcription initiation and elongation (Jonkers et al, 2014; Stasevich et al, 2014). "
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    ABSTRACT: Mammalian transcription occurs stochastically in short bursts interspersed by silent intervals showing a refractory period. However, the underlying processes and consequences on fluctuations in gene products are poorly understood. Here, we use single allele time-lapse recordings in mouse cells to identify minimal models of promoter cycles, which inform on the number and durations of rate-limiting steps responsible for refractory periods. The structure of promoter cycles is gene specific and independent of genomic location. Typically, five rate-limiting steps underlie the silent periods of endogenous promoters, while minimal synthetic promoters exhibit only one. Strikingly, endogenous or synthetic promoters with TATA boxes show simplified two-state promoter cycles. Since transcriptional bursting constrains intrinsic noise depending on the number of promoter steps, this explains why TATA box genes display increased intrinsic noise genome-wide in mammals, as revealed by single-cell RNA-seq. These findings have implications for basic transcription biology and shed light on interpreting single-cell RNA-counting experiments. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.
    Molecular Systems Biology 07/2015; 11(7):823. DOI:10.15252/msb.20156257 · 14.10 Impact Factor
    • "In order to examine if the gene can indeed transcribe to different levels, we fit the data from each time point to a Poisson distribution . Under steady-state or starved conditions, we expected the number of transcripts per active allele to follow a Poisson distribution , meaning that the gene has a single mode of activity (Dar et al., 2012; Senecal et al., 2014). This was the case, pointing to a single transcription mode generating a relatively small amount of mRNA product (Figures 2A and S2A, red and black bars). "
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    ABSTRACT: The transcriptional response of β-actin to extra-cellular stimuli is a paradigm for transcription factor complex assembly and regulation. Serum induction leads to a precisely timed pulse of β-actin transcription in the cell population. Actin protein is proposed to be involved in this response, but it is not known whether cellular actin levels affect nuclear β-actin transcription. We perturbed the levels of key signaling factors and examined the effect on the induced transcriptional pulse by following endogenous β-actin alleles in single living cells. Lowering serum response factor (SRF) protein levels leads to loss of pulse integrity, whereas reducing actin protein levels reveals positive feedback regulation, resulting in elevated gene activation and a prolonged transcriptional response. Thus, transcriptional pulse fidelity requires regulated amounts of signaling proteins, and perturbations in factor levels eliminate the physiological response, resulting in either tuning down or exaggeration of the transcriptional pulse. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Cell Reports 04/2015; 11(3). DOI:10.1016/j.celrep.2015.03.039 · 8.36 Impact Factor
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    • "A simple stochastic model that is widely used in analyzing bursting in gene expression is the random telegraph model that takes into account the switching of promoter between transcriptionally active (ON) and inactive (OFF) states [38] [39] [40]. This model has been used as the basis for several studies focusing on inferring gene expression parameters based on observations of the mean and variance of mRNA/protein distributions [13] [26] [41]. "
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    ABSTRACT: Gene expression in individual cells is highly variable and sporadic, often resulting in the synthesis of mRNAs and proteins in bursts. Bursting in gene expression is known to impact cell-fate in diverse systems ranging from latency in HIV-1 viral infections to cellular 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 processes, highlighting the need for more general stochastic models. To address this issue, we invoke a mapping between general models of gene expression and systems studied in queueing theory to derive exact analytical expressions for the moments associated with mRNA/protein steady-state distributions. These moments are then used to derive explicit conditions, based entirely on experimentally measurable quantities, that determine if the burst distributions deviate from the geometric distribution or if burst arrival deviates from a Poisson process. For non-Poisson arrivals, we develop approaches for accurate estimation of burst parameters.
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