Genome-wide kinetic properties of transcriptional bursting in mouse embryonic stem cells.
ABSTRACT: Transcriptional bursting is the stochastic activation and inactivation of promoters, contributing to cell-to-cell heterogeneity in gene expression. However, the mechanism underlying the regulation of transcriptional bursting kinetics (burst size and frequency) in mammalian cells remains elusive. In this study, we performed single-cell RNA sequencing to analyze the intrinsic noise and mRNA levels for elucidating the transcriptional bursting kinetics in mouse embryonic stem cells. Informatics analyses and functional assays revealed that transcriptional bursting kinetics was regulated by a combination of promoter- and gene body-binding proteins, including the polycomb repressive complex 2 and transcription elongation factors. Furthermore, large-scale CRISPR-Cas9-based screening identified that the Akt/MAPK signaling pathway regulated bursting kinetics by modulating transcription elongation efficiency. These results uncovered the key molecular mechanisms underlying transcriptional bursting and cell-to-cell gene expression noise in mammalian cells.
Project description:Cellular decision-making and environmental adaptation are dependent upon a heterogeneous response of gene expression to external cues. Heterogeneity arises in transcription from random switching between transcriptionally active and inactive states, resulting in bursts of RNA synthesis. Furthermore, the cellular state influences the competency of transcription, thereby globally affecting gene expression in a cell-specific manner. We determined how external stimuli interplay with cellular state to modulate the kinetics of bursting. To this end, single-cell dynamics of nascent transcripts were monitored at the endogenous estrogen-responsive GREB1 locus. Stochastic modeling of gene expression implicated a two-state promoter model in which the estrogen stimulus modulates the frequency of transcriptional bursting. The cellular state affects transcriptional dynamics by altering initiation and elongation kinetics and acts globally, as GREB1 alleles in the same cell correlate in their transcriptional output. Our results suggest that cellular state strongly affects the first step of the central dogma of gene expression, to promote heterogeneity in the transcriptional output of isogenic cells.
Project description:Cell-to-cell variability plays a critical role in cellular responses and decision-making in a population, and transcriptional bursting has been broadly studied by experimental and theoretical approaches as the potential source of cell-to-cell variability. Although molecular mechanisms of transcriptional bursting have been proposed, there is little consensus. An unsolved key question is whether transcriptional bursting is intertwined with many transcriptional regulatory factors or is an intrinsic characteristic of RNA polymerase on DNA. Here we design an in vitro single-molecule measurement system to analyse the kinetics of transcriptional bursting. The results indicate that transcriptional bursting is caused by interplay between RNA polymerases on DNA. The kinetics of in vitro transcriptional bursting is quantitatively consistent with the gene-nonspecific kinetics previously observed in noisy gene expression in vivo. Our kinetic analysis based on a cellular automaton model confirms that arrest and rescue by trailing RNA polymerase intrinsically causes transcriptional bursting.
Project description:How transcriptional bursting relates to gene regulation is a central question that has persisted for more than a decade. Here, we measure nascent transcriptional activity in early Drosophila embryos and characterize the variability in absolute activity levels across expression boundaries. We demonstrate that boundary formation follows a common transcription principle: a single control parameter determines the distribution of transcriptional activity, regardless of gene identity, boundary position, or enhancer-promoter architecture. We infer the underlying bursting kinetics and identify the key regulatory parameter as the fraction of time a gene is in a transcriptionally active state. Unexpectedly, both the rate of polymerase initiation and the switching rates are tightly constrained across all expression levels, predicting synchronous patterning outcomes at all positions in the embryo. These results point to a shared simplicity underlying the apparently complex transcriptional processes of early embryonic patterning and indicate a path to general rules in transcriptional regulation.
Project description:Transcription of highly expressed genes has been shown to occur in stochastic bursts. But the origin of such ubiquitous phenomenon has not been understood. Here, we present the mechanism in bacteria. We developed a high-throughput, in vitro, single-molecule assay to follow transcription on individual DNA templates in real time. We showed that positive supercoiling buildup on a DNA segment by transcription slows down transcription elongation and eventually stops transcription initiation. Transcription can be resumed upon gyrase binding to the DNA segment. Furthermore, using single-cell mRNA counting fluorescence in situ hybridization (FISH), we found that duty cycles of transcriptional bursting depend on the intracellular gyrase concentration. Together, these findings prove that transcriptional bursting of highly expressed genes in bacteria is primarily caused by reversible gyrase dissociation from and rebinding to a DNA segment, changing the supercoiling level of the segment.
Project description:Mammalian genes transcribe RNA not continuously, but in bursts. Transcriptional output can be modulated by altering burst fraction or burst size, but how regulatory elements control bursting parameters remains unclear. Single-molecule RNA FISH experiments revealed that the ?-globin enhancer (LCR) predominantly augments transcriptional burst fraction of the ?-globin gene with modest stimulation of burst size. To specifically measure the impact of long-range chromatin contacts on transcriptional bursting, we forced an LCR-?-globin promoter chromatin loop. We observed that raising contact frequencies increases burst fraction but not burst size. In cells in which two developmentally distinct LCR-regulated globin genes are cotranscribed in cis, burst sizes of both genes are comparable. However, allelic co-transcription of both genes is statistically disfavored, suggesting mutually exclusive LCR-gene contacts. These results are consistent with competition between the ?-type globin genes for LCR contacts and suggest that LCR-promoter loops are formed and released with rapid kinetics.
Project description:Transcription is fundamentally noisy, leading to significant heterogeneity across bacterial populations. Noise is often attributed to burstiness, but the underlying mechanisms and their dependence on the mode of promotor regulation remain unclear. Here, we measure E. coli single cell mRNA levels for two stress responses that depend on bacterial sigma factors with different mode of transcription initiation (?70 and ?54). By fitting a stochastic model to the observed mRNA distributions, we show that the transition from low to high expression of the ?70-controlled stress response is regulated via the burst size, while that of the ?54-controlled stress response is regulated via the burst frequency. Therefore, transcription initiation involving ?54 differs from other bacterial systems, and yields bursting kinetics characteristic of eukaryotic systems.
Project description: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 processes, highlighting the need for analysis of more general stochastic models. To address this issue, we invoke a mapping between general stochastic 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 results are then used to derive noise signatures, i.e. 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. The proposed approaches can lead to new insights into transcriptional bursting based on measurements of steady-state mRNA/protein distributions.
Project description: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.
Project description:Populations of genetically identical cells generally show a large variability in cell phenotypes, which is typically associated with the stochastic nature of gene expression processes. It is widely believed that a significant source of such randomness is transcriptional bursting, which is when periods of active production of RNA molecules alternate with periods of RNA degradation. However, the molecular mechanisms of such strong fluctuations remain unclear. Recent studies suggest that DNA supercoiling, which happens during transcription, might be directly related to the bursting behavior. Stimulated by these observations, we developed a stochastic mechanochemical model of supercoiling-induced transcriptional bursting in which the RNA synthesis leads to the buildup of torsion in DNA. This slows down the RNA production until it is bound by the enzyme gyrase to DNA, which releases the stress and allows for the RNA synthesis to restart with the original rate. Using a thermodynamically consistent coupling between mechanical and chemical processes, the dynamic properties of transcription are explicitly evaluated. In addition, a first-passage method to evaluate the dynamics of transcription is developed. Theoretical analysis shows that transcriptional bursting is observed when both the supercoiling and the mechanical stress release due to gyrase are present in the system. It is also found that the overall RNA production rate is not constant and depends on the number of previously synthesized RNA molecules. A comparison with experimental data on bacteria allows us to evaluate the energetic cost of supercoiling during transcription. It is argued that the relatively weak mechanochemical coupling might allow transcription to be regulated most effectively.
Project description:The dynamics of short-lived mRNA results in bursts of protein production in gene regulatory networks. We investigate the propagation of bursting noise between different levels of mathematical modelling and demonstrate that conventional approaches based on diffusion approximations can fail to capture bursting noise. An alternative coarse-grained model, the so-called piecewise deterministic Markov process (PDMP), is seen to outperform the diffusion approximation in biologically relevant parameter regimes. We provide a systematic embedding of the PDMP model into the landscape of existing approaches, and we present analytical methods to calculate its stationary distribution and switching frequencies.