Rate Of Transcription Initiation Research Articles

Generating information-dense promoter sequences with optimal string packing.

Dense arrangements of binding sites within nucleotide sequences can collectively influence downstream transcription rates or initiate biomolecular interactions. For example, natural promoter regions can harbor many overlapping transcription factor binding sites that influence the rate of transcription initiation. Despite the prevalence of overlapping binding sites in nature, rapid design of nucleotide sequences with many overlapping sites remains a challenge. Here, we show that this is an NP-hard problem, coined here as the nucleotide String Packing Problem (SPP). We then introduce a computational technique that efficiently assembles sets of DNA-protein binding sites into dense, contiguous stretches of double-stranded DNA. For the efficient design of nucleotide sequences spanning hundreds of base pairs, we reduce the SPP to an Orienteering Problem with integer distances, and then leverage modern integer linear programming solvers. Our method optimally packs sets of 20-100 binding sites into dense nucleotide arrays of 50-300 base pairs in 0.05-10 seconds. Unlike approximation algorithms or meta-heuristics, our approach finds provably optimal solutions. We demonstrate how our method can generate large sets of diverse sequences suitable for library generation, where the frequency of binding site usage across the returned sequences can be controlled by modulating the objective function. As an example, we then show how adding additional constraints, like the inclusion of sequence elements with fixed positions, allows for the design of bacterial promoters. The nucleotide string packing approach we present can accelerate the design of sequences with complex DNA-protein interactions. When used in combination with synthesis and high-throughput screening, this design strategy could help interrogate how complex binding site arrangements impact either gene expression or biomolecular mechanisms in varied cellular contexts.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction.

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

Pattern formation along the central dogma by the numbers

In embryonic development, the spatiotemporal information is propagated along the central dogma in order to establish the adult body plan: input transcription factors dictate patterns of transcriptional initiation leading to the formation of cytoplasmic mRNA patterns and culminating in the emergence of protein patterns that endow cells with their ultimate developmental fates. The parameters underlying this transmission of information are of great importance for realizing developmental programs. For example, the magnitudes of the rates of transcription initiation and elongation, and of mRNA and protein diffusion and degradation, and their modulation throughout development, dictate the sharpness and lifetime of each protein pattern in space and time.

Fluorogenic RNA aptamers to probe transcription initiation and co-transcriptional RNA folding by multi-subunit RNA polymerases.

Transcription is the first and most highly regulated step in gene expression. Experimental techniques for monitoring transcription are, thus, important for studying gene expression and gene regulation as well as for translational research and drug development. Fluorescence methods are often superior to other techniques for real-time monitoring of biochemical processes. Green fluorescent proteins have long served as valuable tools for studying the process of translation. Here we present two methods that utilize fluorescent light-up RNA aptamers (FLAPs), the RNA mimics of green fluorescent proteins, to monitoring transcription and co-transcriptional RNA folding. FLAPs adopt defined three-dimensional folds that bind low molecular weight compounds called fluorogens with concomitant increase in fluorescence by many folds. FLAPs provide a strong fluorescence signal with low background that allows monitoring of transcription in real time in vitro and in vivo. However, it takes several seconds for RNA polymerase to synthesize FLAPs and the subsequent folding of the fluorogen-binding platform takes additional seconds or minutes. Here we show that Broccoli-FLAP is well suited for monitoring the rate of transcription initiation in a multi-round setup that mitigates the slow rate of the FLAP maturation. Furthermore, we demonstrate that a relatively slow and inefficient folding of iSpinach-FLAP can be taken advantage of for monitoring the action of RNA folding chaperones.

DNA supercoiling-mediated collective behavior of co-transcribing RNA polymerases.

Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or ‘push’ between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate by modifying the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the DNA torsional response. Using stochastic simulations, we demonstrate DNA supercoiling-mediated long-range cooperation between co-transcribing RNAPs. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern transcriptional dynamics.

Tuning Cell-Free Composition Controls the Time Delay, Dynamics, and Productivity of TX-TL Expression.

The composition of cell-free expression systems (TX-TL) is adjusted by adding macromolecular crowding agents and salts. However, the effects of these cosolutes on the dynamics of individual gene expression processes have not been quantified. Here, we carry out kinetic mRNA and protein level measurements on libraries of genetic constructs using the common cosolutes PEG-8000, Ficoll-400, and magnesium glutamate. By combining these measurements with biophysical modeling, we show that cosolutes have differing effects on transcription initiation, translation initiation, and translation elongation rates with trade-offs between time delays, expression tunability, and maximum expression productivity. We also confirm that biophysical models can predict translation initiation rates in TX-TL using Escherichia coli lysate. We discuss how cosolute composition can be tuned to maximize performance across different cell-free applications, including biosensing, diagnostics, and biomanufacturing.

Live single-cell transcriptional dynamics via RNA labelling during the phosphate response in plants.

Plants are constantly adapting to ambient fluctuations through spatial and temporal transcriptional responses. Here, we implemented the latest-generation RNA imaging system and combined it with microfluidics to visualize transcriptional regulation in living Arabidopsis plants. This enabled quantitative measurements of the transcriptional activity of single loci in single cells, in real time and under changing environmental conditions. Using phosphate-responsive genes as a model, we found that active genes displayed high transcription initiation rates (one initiation event every ~3 s) and frequently clustered together in endoreplicated cells. We observed gene bursting and large allelic differences in single cells, revealing that at steady state, intrinsic noise dominated extrinsic variations. Moreover, we established that transcriptional repression triggered in roots by phosphate, a crucial macronutrient limiting plant development, occurred with unexpectedly fast kinetics (on the order of minutes) and striking heterogeneity between neighbouring cells. Access to single-cell RNA polymerase II dynamics in live plants will benefit future studies of signalling processes.

Co-condensation between transcription factor and coactivator p300 modulates transcriptional bursting kinetics

The coactivator p300/CREB-binding protein (CBP) regulates genes by facilitating the assembly of transcriptional machinery and by acetylating histones and other factors. However, it remains mostly unclear how both functions of p300 are dynamically coordinated during gene control. Here, we showed that p300 can orchestrate two functions through the formation of dynamic clusters with certain transcription factors (TFs), which is mediated by the interactions between a TF's transactivation domain (TAD) and the intrinsically disordered regions of p300. Co-condensation can enable spatially defined, all-or-none activation of p300's catalytic activity, priming the recruitment of coactivators, including Brd4. We showed that co-condensation can modulate transcriptional initiation rate and burst duration of target genes, underlying nonlinear gene regulatory functions. Such modulation is consistent with how p300 might shape gene bursting kinetics globally. Altogether, these results suggest an intriguing gene regulation mechanism, in which TF and p300 co-condensation contributes to transcriptional bursting regulation and cooperative gene control.

Control of ribosome synthesis in bacteria: the important role of rRNA chain elongation rate.

Bacteria growth depends crucially on protein synthesis, which is limited by ribosome synthesis. Ribosomal RNA (rRNA) transcription is the rate-limiting step of ribosome synthesis. It is generally proposed that the transcriptional initiation rate of rRNA operon is the primary factor that controls the rRNA synthesis. In this study, we established a convenient GFP-based reporter approach for measuring the bacterial rRNA chain elongation rate. We showed that the rRNA chain elongation rate of Escherichia coli remains constant under nutrient limitation and chloramphenicol inhibition. In contrast, rRNA chain elongation rate decreases dramatically under low temperatures. Strikingly, we found that Vibrio natriegens, the fastest growing bacteria known, has a 50% higher rRNA chain elongation rate than E. coli, which contributes to its rapid ribosome synthesis. Our study demonstrates that rRNA chain elongation rate is another important factor that affects the bacterial ribosome synthesis capacity.

Orthogonal tuning of gene expression noise using CRISPR-Cas.

The control of gene expression noise is important for improving drug treatment and the performance of synthetic biological systems. Previous work has tuned gene expression noise by changing the rate of transcription initiation, mRNA degradation, and mRNA translation. However, these methods are invasive: they require changes to the target genetic components. Here, we create an orthogonal system based on CRISPR-dCas9 to tune gene expression noise. Specifically, we modulate the gene expression noise of a reporter gene in Escherichia coli by incorporating CRISPR activation and repression (CRISPRar) simultaneously in a single cell. The CRISPRar uses a single dCas9 that recognizes two different single guide RNAs (sgRNA). We build a library of sgRNA variants with different expression activation and repression strengths. We find that expression noise and mean of a reporter gene can be tuned independently by CRISPRar. Our results suggest that the expression noise is tuned by the competition between two sgRNAs that modulate the binding of RNA polymerase to promoters. The CRISPRar may change how we tune expression noise at the genomic level. Our work has broad impacts on the study of gene functions, phenotypical heterogeneity, and genetic circuit control.

Orthogonal tuning of gene expression noise using CRISPR-Cas.

The control of gene expression noise is important for improving drug treatment and the performance of synthetic biological systems. Previous work has tuned gene expression noise by changing the rate of transcription initiation, mRNA degradation, and mRNA translation. However, these methods are invasive: they require changes to the target genetic components. Here, we create an orthogonal system based on CRISPR-dCas9 to tune gene expression noise. Specifically, we modulate the gene expression noise of a reporter gene in Escherichia coli by incorporating CRISPR activation and repression (CRISPRar) simultaneously in a single cell. The CRISPRar uses a single dCas9 that recognizes two different single guide RNAs (sgRNA). We build a library of sgRNA variants with different expression activation and repression strengths. We find that expression noise and mean of a reporter gene can be tuned independently by CRISPRar. Our results suggest that the expression noise is tuned by the competition between two sgRNAs that modulate the binding of RNA polymerase to promoters. The CRISPRar may change how we tune expression noise at the genomic level. Our work has broad impacts on the study of gene functions, phenotypical heterogeneity, and genetic circuit control.

Size-Dependent Increase in RNA Polymerase II Initiation Rates Mediates Gene Expression Scaling with Cell Size.

Cell size varies during the cell cycle and in response to external stimuli. This requires the tight coordination, or "scaling," of mRNA and protein quantities with the cell volume in order to maintain biomolecule concentrations and cell density. Evidence in cell populations and single cells indicates that scaling relies on the coordination of mRNA transcription rates with cell size. Here, we use a combination of single-molecule fluorescence in situ hybridization (smFISH), time-lapse microscopy, and mathematical modeling in single fission yeast cells to uncover the precise molecular mechanisms that control transcription rates scaling with cell size. Linear scaling of mRNA quantities is apparent in single fission yeast cells during a normal cell cycle. Transcription of both constitutive and periodic genes is a Poisson process with transcription rates scaling with cell size and without evidence for transcriptional off states. Modeling and experimental data indicate that scaling relies on the coordination of RNA polymerase II (RNAPII) transcription initiation rates with cell size and that RNAPII is a limiting factor. We show using real-time quantitative imaging that size increase is accompanied by a rapid concentration-independent recruitment of RNAPII onto chromatin. Finally, we find that, in multinucleated cells, scaling is set at the level of single nuclei and not the entire cell, making the nucleus a determinant of scaling. Integrating our observations in a mechanistic model of RNAPII-mediated transcription, we propose that scaling of gene expression with cell size is the consequence of competition between genes for limiting RNAPII.

MeCP2 Represses the Rate of Transcriptional Initiation of Highly Methylated Long Genes.

Mutations in the methyl-DNA-binding repressor protein MeCP2 cause the devastating neurodevelopmental disorder Rett syndrome. It has been challenging to understand how MeCP2 regulates transcription because MeCP2 binds broadly across the genome and MeCP2 mutations are associated with widespread small-magnitude changes in neuronal gene expression. We demonstrate here that MeCP2 represses nascent RNA transcription of highly methylated long genes in the brain through its interaction with the NCoR co-repressor complex. By measuring the rates of transcriptional initiation and elongation directly in the brain, we find that MeCP2 has no measurable effect on transcriptional elongation, but instead represses the rate at which Pol II initiates transcription of highly methylated long genes. These findings suggest a new model of MeCP2 function in which MeCP2 binds broadly across highly methylated regions of DNA, but acts at transcription start sites to attenuate transcriptional initiation.

Measuring transcription at a single gene copy reveals hidden drivers of bacterial individuality.

Single-cell measurements of mRNA copy-number inform our understanding of stochastic gene expression [1-3], but these measurements coarse-grain over the individual copies of the gene, where transcription and its regulation stochastically take plasce [4, 5]. Here we combine single-molecule quantification of mRNA and gene loci to measure the transcriptional activity of an endogenous gene in individual Escherichia coli bacteria. Interpreted using a theoretical model for mRNA dynamics, the single-cell data allows us to obtain the probabilistic rates of promoter switching, transcription initiation and elongation, mRNA release and degradation. Unexpectedly, we find that gene activity can be strongly coupled to the transcriptional state of another copy of the same gene present in the cell, and to the event of gene replication during the bacterial cell cycle. These gene-copy and cell-cycle correlations demonstrate the limits of mapping whole-cell mRNA numbers to the underlying stochastic gene activity, and instead highlight the contribution of previously hidden variables to the observed population heterogeneity.

Dynamics of transcriptional (re)-programming of syncytial nuclei in developing muscles

BackgroundA stereotyped array of body wall muscles enables precision and stereotypy of animal movements. In Drosophila, each syncytial muscle forms via fusion of one founder cell (FC) with multiple fusion competent myoblasts (FCMs). The specific morphology of each muscle, i.e. distinctive shape, orientation, size and skeletal attachment sites, reflects the specific combination of identity transcription factors (iTFs) expressed by its FC. Here, we addressed three questions: Are FCM nuclei naive? What is the selectivity and temporal sequence of transcriptional reprogramming of FCMs recruited into growing syncytium? Is transcription of generic myogenic and identity realisation genes coordinated during muscle differentiation?ResultsThe tracking of nuclei in developing muscles shows that FCM nuclei are competent to be transcriptionally reprogrammed to a given muscle identity, post fusion. In situ hybridisation to nascent transcripts for FCM, FC-generic and iTF genes shows that this reprogramming is progressive, beginning by repression of FCM-specific genes in fused nuclei, with some evidence that FC nuclei retain specific characteristics. Transcription of identity realisation genes is linked to iTF activation and regulated at levels of both transcription initiation rate and period of transcription. The generic muscle differentiation programme is activated independently.ConclusionsTranscription reprogramming of fused myoblast nuclei is progressive, such that nuclei within a syncytial fibre at a given time point during muscle development are heterogeneous with regards to specific gene transcription. This comprehensive view of the dynamics of transcriptional (re)programming of post-mitotic nuclei within syncytial cells provides a new framework for understanding the transcriptional control of the lineage diversity of multinucleated cells.

A damaged genome\u2019s transcriptional landscape through multilayered expression profiling around in situ-mapped DNA double-strand breaks

Of the many types of DNA damage, DNA double-strand breaks (DSBs) are probably the most deleterious. Mounting evidence points to an intricate relationship between DSBs and transcription. A cell system in which the impact on transcription can be investigated at precisely mapped genomic DSBs is essential to study this relationship. Here in a human cell line, we map genome-wide and at high resolution the DSBs induced by a restriction enzyme, and we characterize their impact on gene expression by four independent approaches by monitoring steady-state RNA levels, rates of RNA synthesis, transcription initiation and RNA polymerase II elongation. We consistently observe transcriptional repression in proximity to DSBs. Downregulation of transcription depends on ATM kinase activity and on the distance from the DSB. Our study couples for the first time, to the best of our knowledge, high-resolution mapping of DSBs with multilayered transcriptomics to dissect the events shaping gene expression after DSB induction at multiple endogenous sites.

Differential expression pattern of transcription factors across annual Medicago genotypes in response to salinity stress

Plants respond differently to salinity stress due to their unique gene architectures. Among genes, transcription factors (TFs) regulate many physiological and biochemical processes by modulating the rate of transcription initiation of target genes. Modulation of TFs has been correlated to the salt adaptation of any given genotype. In order to identify the expression of eight TFs (belong to bHLH, CBF, MYB, WRKY, and Zpt2 families) in three annual Medicago genotypes (M. polymorpha cv. Ieze, M. laciniata cv. Shushtar, and M. laciniata cv. Gheshm) under salinity stress, the RT-qPCR analyses were performed. Attempts were also made to establish relationships between gene expression profiles and morpho-physiological traits in these genotypes. In response to salinity, cv. Ieze had minimal changes in biomass, the electrolyte leakage, H2O2 content, and the higher ratio of reduced to oxidized glutathione than the other genotypes. Furthermore, Ieze had lower accumulation of Na+ and less decrease in K+ content. Altogether, it is concluded that Ieze could be regarded as a salt tolerant genotype. Transcriptome profile showed considerable variation across Medicago genotypes and among plant tissues. Among five TFs, Zpt2-2 and CBF4 had higher expression in salt-tolerant genotypes suggesting these genes as good candidates in genetic improvement programs to produce stress-tolerant plants.

Absolute quantitative measurement of transcriptional kinetic parametersin vivo

mRNA expression involves transcription initiation, elongation and degradation. In cells, these dynamic processes are highly regulated. However, experimental characterization of the dynamic processes in vivo is difficult due to the paucity of methods capable of direct measurements. We present a highly sensitive and versatile method enabling direct characterization of the dynamic processes. Our method is based on single-molecule fluorescence in situ hybridization (smFISH) and quantitative analyses of hybridization signals. We hybridized multiple probes labelled with spectrally distinct fluorophores to multiple sub-regions of single mRNAs, and visualized the kinetics of synthesis and degradation of the sub-regions. Quantitative analyses of the data lead to absolute quantification of the lag time of mRNA induction (the time it takes for external signals to activate transcription initiation), transcription initiation rate, transcription elongation speed (i.e. mRNA chain-growth speed), the rate of premature termination of transcripts and degradation rates. Applying our method to three different biological problems, we demonstrated how our method may be applicable to reveal dynamics of mRNA expression that was difficult to study previously. We expect such absolute quantification can greatly facilitate understanding of gene expression and its regulation working at the levels of transcriptional initiation, elongation and degradation.

Deciphering Transcriptional Dynamics In Vivo by Counting Nascent RNA Molecules

Deciphering how the regulatory DNA sequence of a gene dictates its expression in response to intra and extracellular cues is one of the leading challenges in modern genomics. The development of novel single-cell sequencing and imaging techniques, as well as a better exploitation of currently available single-molecule imaging techniques, provides an avenue to interrogate the process of transcription and its dynamics in cells by quantifying the number of RNA polymerases engaged in the transcription of a gene (or equivalently the number of nascent RNAs) at a given moment in time. In this paper, we propose that measurements of the cell-to-cell variability in the number of nascent RNAs provide a mostly unexplored method for deciphering mechanisms of transcription initiation in cells. We propose a simple kinetic model of transcription initiation and elongation from which we calculate nascent RNA copy-number fluctuations. To demonstrate the usefulness of this approach, we test our theory against published nascent RNA data for twelve constitutively expressed yeast genes. Rather than transcription being initiated through a single rate limiting step, as it had been previously proposed, our single-cell analysis reveals the presence of at least two rate limiting steps. Surprisingly, half of the genes analyzed have nearly identical rates of transcription initiation, suggesting a common mechanism. Our analytical framework can be used to extract quantitative information about dynamics of transcription from single-cell sequencing data, as well as from single-molecule imaging and electron micrographs of fixed cells, and provides the mathematical means to exploit the quantitative power of these technologies.