Frequency Of Transcription Initiation Research Articles

Position-dependent function of human sequence-specific transcription factors.

Patterns of transcriptional activity are encoded in our genome through regulatory elements such as promoters or enhancers that, paradoxically, contain similar assortments of sequence-specific transcription factor (TF)binding sites1-3. Knowledge of how these sequence motifs encode multiple, often overlapping, gene expression programs is central to understanding gene regulation and how mutations in non-coding DNA manifest in disease4,5. Here, by studying gene regulation from the perspective of individual transcription start sites (TSSs), using natural genetic variation, perturbation of endogenous TF protein levels and massively parallel analysis of natural and synthetic regulatory elements, we show that the effect of TF binding on transcription initiation is position dependent. Analysing TF-binding-site occurrences relative to the TSS, we identified several motifs with highly preferential positioning. We show that these patterns are a combination of a TF's distinct functional profiles-many TFs, including canonical activators such as NRF1, NFY and Sp1, activate or repress transcription initiation depending on their precise position relative to the TSS. As such, TFs and their spacing collectively guide the site and frequency of transcription initiation. More broadly, these findings reveal how similar assortments of TFbinding sites can generate distinct gene regulatory outcomes depending on their spatial configuration and how DNA sequence polymorphisms may contribute to transcription variation and disease and underscore a critical role for TSS data in decoding the regulatory information of our genome.

ProD: A Tool for Predictive Design of Tailored Promoters in Escherichia coli.

A major goal in synthetic biology is the engineering of synthetic gene circuits with a predictable, controlled and designed outcome. This creates a need for building blocks that can modulate gene expression without interference with the native cell system. A tool allowing forward engineering of promoters with predictable transcription initiation frequency is still lacking. Promoter libraries specific for σ70 to ensure the orthogonality of gene expression were built in Escherichia coli and labeled using fluorescence-activated cell sorting to obtain high-throughput DNA sequencing data to train a convolutional neural network. We were able to confirm in vivo that the model is able to predict the promoter transcription initiation frequency (TIF) of new promoter sequences. Here, we provide an online tool for promoter design (ProD) in E. coli, which can be used to tailor output sequences of desired promoter TIF or predict the TIF of a custom sequence.

The Hda1 histone deacetylase limits divergent non-coding transcription and restricts transcription initiation frequency.

Nucleosome‐depleted regions (NDRs) at gene promoters support initiation of RNA polymerase II transcription. Interestingly, transcription often initiates in both directions, resulting in an mRNA and a divergent non‐coding (DNC) transcript of unclear purpose. Here, we characterized the genetic architecture and molecular mechanism of DNC transcription in budding yeast. Using high‐throughput reverse genetic screens based on quantitative single‐cell fluorescence measurements, we identified the Hda1 histone deacetylase complex (Hda1C) as a repressor of DNC transcription. Nascent transcription profiling showed a genome‐wide role of Hda1C in repression of DNC transcription. Live‐cell imaging of transcription revealed that mutations in the Hda3 subunit increased the frequency of DNC transcription. Hda1C contributed to decreased acetylation of histone H3 in DNC transcription regions, supporting DNC transcription repression by histone deacetylation. Our data support the interpretation that DNC transcription results as a consequence of the NDR‐based architecture of eukaryotic promoters, but that it is governed by locus‐specific repression to maintain genome fidelity.

PRC1 drives Polycomb-mediated gene repression by controlling transcription initiation and burst frequency.

The Polycomb repressive system plays a fundamental role in controlling gene expression during mammalian development. To achieve this, Polycomb repressive complexes 1 and 2 (PRC1 and PRC2) bind target genes and use histone modification-dependent feedback mechanisms to form Polycomb chromatin domains and repress transcription. The inter-relatedness of PRC1 and PRC2 activity at these sites has made it difficult to discover the specific components of Polycomb chromatin domains that drive gene repression and to understand mechanistically how this is achieved. Here, by exploiting rapid degron-based approaches and time-resolved genomics, we kinetically dissect Polycomb-mediated repression and discover that PRC1 functions independently of PRC2 to counteract RNA polymerase II binding and transcription initiation. Using single-cell gene expression analysis, we reveal that PRC1 acts uniformly within the cell population and that repression is achieved by controlling transcriptional burst frequency. These important new discoveries provide a mechanistic and conceptual framework for Polycomb-dependent transcriptional control.

Predictive design of sigma factor-specific promoters

To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host’s cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.

Cap Analysis of Gene Expression (CAGE): A Quantitative and Genome-Wide Assay of Transcription Start Sites.

Cap analysis of gene expression (CAGE) is an approach to identify and monitor the activity (transcription initiation frequency) of transcription start sites (TSSs) at single base-pair resolution across the genome. It has been effectively used to identify active promoter and enhancer regions in cancer cells, with potential utility to identify key factors to immunotherapy. Here, we overview a series of CAGE protocols and describe detailed experimental steps of the latest protocol based on the Illumina sequencing platform; both experimental steps (see Subheadings 3.1-3.11) and computational processing steps (see Subheadings 3.12-3.20) are described.

The pause-initiation limit restricts transcription activation in human cells

Eukaryotic gene transcription is often controlled at the level of RNA polymerase II (Pol II) pausing in the promoter-proximal region. Pausing Pol II limits the frequency of transcription initiation (‘pause-initiation limit’), predicting that the pause duration must be decreased for transcriptional activation. To test this prediction, we conduct a genome-wide kinetic analysis of the heat shock response in human cells. We show that the pause-initiation limit restricts transcriptional activation at most genes. Gene activation generally requires the activity of the P-TEFb kinase CDK9, which decreases the duration of Pol II pausing and thereby enables an increase in the productive initiation frequency. The transcription of enhancer elements is generally not pause limited and can be activated without CDK9 activity. Our results define the kinetics of Pol II transcriptional regulation in human cells at all gene classes during a natural transcription response.

Opposing chromatin remodelers control transcription initiation frequency and start site selection.

Precise nucleosome organization at eukaryotic promoters is thought to be generated by multiple chromatin remodeler (CR) enzymes and to affect transcription initiation. Using an integrated analysis of chromatin remodeler binding and nucleosome occupancy following rapid remodeler depletion, we investigated the interplay between these enzymes and their impact on transcription in yeast. We show that many promoters are affected by multiple CRs that operate in concert or in opposition to position the key transcription start site (TSS)-associated +1 nucleosome. We also show that nucleosome movement after CR inactivation usually results from the activity of another CR and that in the absence of any remodeling activity, +1 nucleosomes largely maintain their positions. Finally, we present functional assays suggesting that +1 nucleosome positioning often reflects a trade-off between maximizing RNA polymerase recruitment and minimizing transcription initiation at incorrect sites. Our results provide a detailed picture of fundamental mechanisms linking promoter nucleosome architecture to transcription initiation.

CDK9-dependent RNA polymerase II pausing controls transcription initiation.

Gene transcription can be activated by decreasing the duration of RNA polymerase II pausing in the promoter-proximal region, but how this is achieved remains unclear. Here we use a 'multi-omics' approach to demonstrate that the duration of polymerase pausing generally limits the productive frequency of transcription initiation in human cells ('pause-initiation limit'). We further engineer a human cell line to allow for specific and rapid inhibition of the P-TEFb kinase CDK9, which is implicated in polymerase pause release. CDK9 activity decreases the pause duration but also increases the productive initiation frequency. This shows that CDK9 stimulates release of paused polymerase and activates transcription by increasing the number of transcribing polymerases and thus the amount of mRNA synthesized per time. CDK9 activity is also associated with long-range chromatin interactions, suggesting that enhancers can influence the pause-initiation limit to regulate transcription.

Nitrous oxide production and consumption: regulation of gene expression by gas-sensitive transcription factors

Several biochemical mechanisms contribute to the biological generation of nitrous oxide (N(2)O). N(2)O generating enzymes include the respiratory nitric oxide (NO) reductase, an enzyme from the flavo-diiron family, and flavohaemoglobin. On the other hand, there is only one enzyme that is known to use N(2)O as a substrate, which is the respiratory N(2)O reductase typically found in bacteria capable of denitrification (the respiratory reduction of nitrate and nitrite to dinitrogen). This article will briefly review the properties of the enzymes that make and consume N(2)O, together with the accessory proteins that have roles in the assembly and maturation of those enzymes. The expression of the genes encoding the enzymes that produce and consume N(2)O is regulated by environmental signals (typically oxygen and NO) acting through regulatory proteins, which, either directly or indirectly, control the frequency of transcription initiation. The roles and mechanisms of these proteins, and the structures of the regulatory networks in which they participate will also be reviewed.

Restrained expression, a method to overproduce toxic membrane proteins by exploiting operator–repressor interactions

A major rate-limiting step in determining structures of membrane proteins is heterologous protein production. Toxicity often associated with rapid overexpression results in reduced biomass along with low yields of target protein. Mitigation of toxic effects was achieved using a method we call "restrained expression," a controlled reduction in the frequency of transcription initiation by exploiting the infrequent transitions of Lac repressor to a free state from its complex with the lac-operator site within a T7lac promoter that occur in the absence of the inducer isopropyl β-D-1-thiogalactopyranoside. In addition, production of the T7 RNA polymerase that drives transcription of the target is limited using the tightly regulated arabinose promoter in Escherichia coli strain BL21-AI. Using this approach, we can achieve a 200-fold range of green fluorescent protein expression levels. Application to members of a family of ion pumps results in 5- to 25-fold increases in expression over the benchmark BL21(DE3) host strain. A viral ion channel highly toxic to E. coli can also be overexpressed. In comparative analyses, restrained expression outperforms commonly used E. coli expression strategies. The mechanism underlying improved target protein yield arises from minimization of protein aggregation and proteolysis that reduce membrane integrity and cell viability. This study establishes a method to overexpress toxic proteins.

Investigating Co-Regulation Networks using Generative Models

Proteins, often referred to as the ‘workhorses of the cell’;, are produced through the process of gene expression, during which an organism turns its genetic code (DNA) into functional units. Regulation of this expression process increases the versatility of an organism, allows for adaptation to the environment, and in-creases the efficiency with which resources are metabolized by controlling when and in what quantities RNA molecules and proteins are pro-duced. Many diseases are related to failures in one or more components of this system. Examining regulation helps us to understand how an organism evolves and develops, and how malfunctions may break down this process. Much of the control of gene expression is believed to occur by the cell's adjustment of tran-scription initiation frequency. This level of control is carried out by transcription factors (TFs), and transcription factor networks (TFNs) can be used to describe the interactions between these transcription factors and their target genes. In this work we use generative networks to model the creation of TFNs during evolution in order to understand how these networks form and develop. In par-ticular, we examine how the number of TF partners (those that regulate common genes) scales with the number of genes a TF regulates. It has been observed that in several model organisms the degree distribution of this partnership net-work appears to follow an exponential saturation curve. The co-regulatory net-work of our generative model shows a trend similar to that of the model organ-isms. We show that through various modifications to our model we are able to identify the necessary conditions for this observed saturation curve characteristic. This indicates that the saturation curve seen in these co-regulatory networks could be a product of evolutionary development, during which regulators gain and lose interactions with targets over time.

Nuclear Run-On Assay: Figure 1.

The nuclear run-on assay was developed as a method for establishing that the transcription initiation rate contributes to the regulated expression of mammalian genes. The difference between monitoring gene expression by the nuclear run-on assay versus most other assays is that the nuclear run-on assay provides a measure of the frequency of transcription initiation and is largely independent of the effects of RNA stability. It can also be used to determine whether polymerase pausing or attenuation contributes to gene regulation. Briefly, the nuclear run-on assay begins with samples of cells that contain different steady-state amounts of the mRNA or protein of interest. The cells are chilled, and the plasmid membranes are permeabilized or lysed. These steps result in polymerase pausing. The nuclei are then incubated for a short time at 37 degrees C in the presence of nucleoside triphosphates (NTPs) and radiolabeled uridine 5'-triphosphate (UTP). New transcripts are not initiated during this incubation, but the radiolabeled nucleotide becomes incorporated into transcripts that were being synthesized when the cells were first chilled and lysed. The number of nascent transcripts on the gene at the time of chilling is thought to be proportional to the frequency of transcription initiation. To determine the relative number of nascent transcripts in each sample, the radiolabeled RNA is purified and hybridized to a membrane containing immobilized DNA from the gene of interest. The amount of radioactivity that hybridizes to the membrane is approximately proportional to the number of nascent transcripts.

IHF-binding sites inhibit DNA loop formation and transcription initiation

Transcriptional activation of enhancer and σ54-dependent promoters requires efficient interactions between enhancer-binding proteins (EBP) and promoter bound σ54-RNA polymerase (Eσ54) achieved by DNA looping, which is usually facilitated by the integration host factor (IHF). Since the lengths of the intervening region supporting DNA-loop formation are similar among IHF-dependent and IHF-independent promoters, the precise reason(s) why IHF is selectively important for the frequency of transcription initiation remain unclear. Here, using kinetic cyclization and in vitro transcription assays we show that, in the absence of IHF protein, the DNA fragments containing an IHF-binding site have much less looping-formation ability than those that lack an IHF-binding site. Furthermore, when an IHF consensus-binding site was introduced into the intervening region between promoter and enhancer of the target DNA fragments, loop formation and DNA-loop-dependent transcriptional activation are significantly reduced in a position-independent manner. DNA-looping-independent transcriptional activation was unaffected. The binding of IHF to its consensus site in the target promoters clearly restored efficient DNA looping formation and looping-dependent transcriptional activation. Our data provide evidence that one function for the IHF protein is to release a communication block set by intrinsic properties of the IHF DNA-binding site.

A reduction in RNA polymerase II initiation rate suppresses hyper-recombination and transcription-elongation impairment of THO mutants

Hrs1/Med3, a component of the Mediator involved in transcription initiation, was previously isolated as a suppressor of hpr1Delta hyper-recombination linked to transcription elongation. Here we show that hrs1Delta-mediated suppression is specific of transcription-associated hyper-recombination (TAR). The decrease in recombination associated with hrs1Delta, either in wild-type or hpr1Delta cells is only observed in DNA repeats constructs in which transcription is Hrs1-dependent. We propose that the suppression of THO mutants by hrs1Delta is due to the specific effect of hrs1Delta on transcription initiation of the recombination system. In parallel we show that the higher the transcription of a gene the more important becomes the THO complex for its expression, implying that the in vivo relevance of this complex is dependent on the frequency of RNAPII transcription initiation. This study furthers the understanding of the importance of THO in transcription and the maintenance of genome stability.

Molecular Mechanisms Underlying the Positive Stringent Response of the Bacillus subtilis ilv-leu Operon, Involved in the Biosynthesis of Branched-Chain Amino Acids

Branched-chain amino acids are the most abundant amino acids in proteins. The Bacillus subtilis ilv-leu operon is involved in the biosynthesis of branched-chain amino acids. This operon exhibits a RelA-dependent positive stringent response to amino acid starvation. We investigated this positive stringent response upon lysine starvation as well as decoyinine treatment. Deletion analysis involving various lacZ fusions revealed two molecular mechanisms underlying the positive stringent response of ilv-leu, i.e., CodY-dependent and -independent mechanisms. The former is most likely triggered by the decrease in the in vivo concentration of GTP upon lysine starvation, GTP being a corepressor of the CodY protein. So, the GTP decrease derepressed ilv-leu expression through detachment of the CodY protein from its cis elements upstream of the ilv-leu promoter. By means of base substitution and in vitro transcription analyses, the latter (CodY-independent) mechanism was found to comprise the modulation of the transcription initiation frequency, which likely depends on fluctuation of the in vivo RNA polymerase substrate concentrations after stringent treatment, and to involve at least the base species of adenine at the 5' end of the ilv-leu transcript. As discussed, this mechanism is presumably distinct from that for B. subtilis rrn operons, which involves changes in the in vivo concentration of the initiating GTP.

The Effect of Transcription and Translation Initiation Frequencies on the Stochastic Fluctuations in Prokaryotic Gene Expression

The kinetics of prokaryotic gene expression has been modelled by the Monte Carlo computer simulation algorithm of Gillespie, which allowed the study of random fluctuations in the number of protein molecules during gene expression. The model, when applied to the simulation of LacZ gene expression, is in good agreement with experimental data. The influence of the frequencies of transcription and translation initiation on random fluctuations in gene expression has been studied in a number of simulations in which promoter and ribosome binding site effectiveness has been changed in the range of values reported for various prokaryotic genes. We show that the genes expressed from strong promoters produce the protein evenly, with a rate that does not vary significantly among cells. The genes with very weak promoters express the protein in "bursts" occurring at random time intervals. Therefore, if the low level of gene expression results from the low frequency of transcription initiation, huge fluctuations arise. In contrast, the protein can be produced with a low and uniform rate if the gene has a strong promoter and a slow rate of ribosome binding (a weak ribosome binding site). The implications of these findings for the expression of regulatory proteins are discussed.

MalR-mediated Regulation of the Streptococcus pneumoniae malMP Operon at PromoterPM: INFLUENCE OF A PROXIMAL DIVERGENT PROMOTER REGION AND COMPETITION BETWEEN MalR AND RNA POLYMERASE PROTEINS

The Streptococcus pneumoniae mal regulon contains two operons, malXCD and malMP involved in the uptake and utilization of maltosaccharides. Both operons are transcribed from two divergent promoters, P(X) and P(M), and are negatively regulated by the MalR transcriptional repressor. Purified MalR protein binds to two DNA regions that encompasses both promoters, thus occupying its two operators, O(M) and O(X). However, the levels of occupation and repression were different, being higher when MalR was bound to O(M) than when it was anchored to O(X). Competition experiments between MalR and the Escherichia coli RNA polymerase on promoters P(M) and P(X) showed that the affinity of either protein for the promoter/operator DNA sequences was important to determine the frequency of transcription initiation. In addition to the control exerted by MalR, expression from promoter P(M) was affected by upstream sequences located within or close to P(X) promoter.

Discrete promoter elements affect specific properties of RNA polymerase II transcription complexes.

The frequency of transcription initiation at specific RNA polymerase II promoters is, in many cases, related to the ability of the promoter to recruit the transcription machinery to a specific site. However, there may also be functional differences in the properties of assembled transcription complexes that are promoter-specific or regulator-dependent and affect their activity. Transcription complexes formed on variants of the adenovirus major late (AdML) promoter were found to differ in several ways. Mutations in the initiator element increased the sarkosyl sensitivity of the rate of elongation and decreased the rate of early steps in initiation as revealed by a sarkosyl challenge assay that exploited the resistance of RNA synthesis to high concentrations of sarkosyl after formation of one or two phospho-diester bonds. Similar, but clearly distinct, effects were also observed after deletion of the binding site for upstream stimulatory factor from the AdML promoter. In contrast, deletion of binding sites for nuclear factor 1 and Oct-1, as well as mutations in the recognition sequence for initiation site binding protein, were without apparent effect on transcription complexes on templates containing the mouse mammary tumor virus promoter.

Contributions of the TATA box sequence to rate-limiting steps in transcription initiation by RNA polymerase II

We have examined the role of the TATA box in determining transcription initiation frequency in vitro by studying a collection of promoters containing different TATA sequences in the context of the adenovirus major late promoter. In addition to measuring transcription rates, we have determined how the sequence changes affected the association and dissociation kinetics and the affinity of TBP binding. We observed that transcription from promoters containing the highest affinity TATA boxes is limited by the rate with which TBP associates with the promoter. In contrast, transcription from promoters containing lower affinity TATA boxes appears to be limited both by how much TBP is bound and by the relatively low occupancy of the conformation that can undergo subsequent steps in preinitiation complex assembly. The implications of these results in understanding the mechanism of transcription enhancement by transcriptional activators is discussed.