Influence of secondary structure on recovery from pauses during early stages of RNA transcription

Theoretical study of RNA-polymerase behavior considering the backtracking state

The dynamical behavior of the RNA polymerase in the transcription process is vital to gene expression. During the transcription process, the 3' end of the transcribed RNA can be dislocated from the active site of the enzyme and as a result, the RNA polymerase goes to the backtracked state. Here, we develop a theoretical model to study the transcription process considering the backtracking state. We aim at describing the behavior of the enzyme in the backtracking state in the presence of an external force, which leads to two possibilities: (i) rescuing from the backtracking state and, (ii) the arresting of the enzyme. We study the probability and the rate of the mentioned processes. In addition, we find that entering the backtracking state behaves like the Brownian ratchet mechanism. This model could shed some light on the modeling of the transcription process and further studies on the energy landscape of the backtracking channel and the gene regulation.

Transcription Regulation Through Nascent RNA Folding

Folding of RNA into secondary structures through intramolecular base pairing determines an RNA's three-dimensional architecture and associated function. Simple RNA structures like stem loops can provide specialized functions independent of coding capacity, such as protein binding, regulation of RNA processing and stability, stimulation or inhibition of translation. RNA catalysis is dependent on tertiary structures found in the ribosome, tRNAs and group I and II introns. While the extent to which non-coding RNAs contribute to cellular maintenance is generally appreciated, the fact that both non-coding and coding RNA can assume relevant structural states has only recently gained attention. In particular, the co-transcriptional folding of nascent RNA of all classes has the potential to regulate co-transcriptional processing, RNP (ribonucleoprotein particle) formation, and transcription itself. Riboswitches are established examples of co-transcriptionally folded coding RNAs that directly regulate transcription, mainly in prokaryotes. Here we discuss recent studies in both prokaryotes and eukaryotes showing that structure formation may carry a more widespread regulatory logic during RNA synthesis. Local structures forming close to the catalytic center of RNA polymerases have the potential to regulate transcription by reducing backtracking. In addition, stem loops or more complex structures may alter co-transcriptional RNA processing or its efficiency. Several examples of functional structures have been identified to date, and this review provides an overview of physiologically distinct processes where co-transcriptionally folded RNA plays a role. Experimental approaches such as single-molecule FRET and in vivo structural probing to further advance our insight into the significance of co-transcriptional structure formation are discussed.

Nascent RNA and the Coordination of Splicing with Transcription

At each active protein-encoding gene, nascent RNA is tethered to the DNA axis by elongating RNA polymerase II (Pol II) and is continuously altered by splicing and other processing events during its synthesis. This review discusses the development of three major methods that enable us to track the conversion of precursor messenger RNA (pre-mRNA) to messenger RNA (mRNA) products in vivo: live-cell imaging, metabolic labeling of RNA, and RNA-seq of purified nascent RNA. These approaches are complementary, addressing distinct issues of transcription rates and intron lifetimes alongside spatial information regarding the gene position of Pol II at which spliceosomes act. The findings will be placed in the context of active transcription units, each of which-because of the presence of nascent RNA, Pol II, and features of the chromatin environment-will recruit a potentially gene-specific constellation of RNA binding proteins and processing machineries.

Transcription factor regulation of RNA polymerase's torque generation capacity

During transcription, RNA polymerase (RNAP) supercoils DNA as it translocates. The resulting torsional stress in DNA can accumulate and, in the absence of regulatory mechanisms, becomes a barrier to RNAP elongation, causing RNAP stalling, backtracking, and transcriptional arrest. Here we investigate whether and how a transcription factor may regulate both torque-induced Escherichia coli RNAP stalling and the torque generation capacity of RNAP. Using a unique real-time angular optical trapping assay, we found that RNAP working against a resisting torque was highly prone to extensive backtracking. We then investigated transcription in the presence of GreB, a transcription factor known to rescue RNAP from the backtracked state. We found that GreB greatly suppressed RNAP backtracking and remarkably increased the torque that RNAP was able to generate by 65%, from 11.2 pN⋅nm to 18.5 pN·nm. Variance analysis of the real-time positional trajectories of RNAP after a stall revealed the kinetic parameters of backtracking and GreB rescue. These results demonstrate that backtracking is the primary mechanism by which torsional stress limits transcription and that the transcription factor GreB effectively enhances the torsional capacity of RNAP. These findings suggest a broader role for transcription factors in regulating RNAP functionality and elongation.

Optical tweezers studies of transcription by eukaryotic RNA polymerases

Transcription is the first step in the expression of genetic information and it is carried out by large macromolecular enzymes called RNA polymerases. Transcription has been studied for many years and with a myriad of experimental techniques, ranging from bulk studies to high-resolution transcript sequencing. In this review, we emphasise the advantages of using single-molecule techniques, particularly optical tweezers, to study transcription dynamics. We give an overview of the latest results in the single-molecule transcription field, focusing on transcription by eukaryotic RNA polymerases. Finally, we evaluate recent quantitative models that describe the biophysics of RNA polymerase translocation and backtracking dynamics.

Stochastic resetting in backtrack recovery by RNA polymerases

Transcription is a key process in gene expression, in which RNA polymerases produce a complementary RNA copy from a DNA template. RNA polymerization is frequently interrupted by backtracking, a process in which polymerases perform a random walk along the DNA template. Recovery of polymerases from the transcriptionally inactive backtracked state is determined by a kinetic competition between one-dimensional diffusion and RNA cleavage. Here we describe backtrack recovery as a continuous-time random walk, where the time for a polymerase to recover from a backtrack of a given depth is described as a first-passage time of a random walker to reach an absorbing state. We represent RNA cleavage as a stochastic resetting process and derive exact expressions for the recovery time distributions and mean recovery times from a given initial backtrack depth for both continuous and discrete-lattice descriptions of the random walk. We show that recovery time statistics do not depend on the discreteness of the DNA lattice when the rate of one-dimensional diffusion is large compared to the rate of cleavage.

Mechanisms of backtrack recovery by RNA polymerases I and II

During DNA transcription, RNA polymerases often adopt inactive backtracked states. Recovery from backtracks can occur by 1D diffusion or cleavage of backtracked RNA, but how polymerases make this choice is unknown. Here, we use single-molecule optical tweezers experiments and stochastic theory to show that the choice of a backtrack recovery mechanism is determined by a kinetic competition between 1D diffusion and RNA cleavage. Notably, RNA polymerase I (Pol I) and Pol II recover from shallow backtracks by 1D diffusion, use RNA cleavage to recover from intermediary depths, and are unable to recover from extensive backtracks. Furthermore, Pol I and Pol II use distinct mechanisms to avoid nonrecoverable backtracking. Pol I is protected by its subunit A12.2, which decreases the rate of 1D diffusion and enables transcript cleavage up to 20 nt. In contrast, Pol II is fully protected through association with the cleavage stimulatory factor TFIIS, which enables rapid recovery from any depth by RNA cleavage. Taken together, we identify distinct backtrack recovery strategies of Pol I and Pol II, shedding light on the evolution of cellular functions of these key enzymes.

DksA guards elongating RNA polymerase against ribosome-stalling-induced arrest

In bacteria, translation-transcription coupling inhibits RNA polymerase (RNAP) stalling. We present evidence suggesting that, upon amino acid starvation, inactive ribosomes promote rather than inhibit RNAP stalling. We developed an algorithm to evaluate genome-wide polymerase progression independently of local noise and used it to reveal that the transcription factor DksA inhibits promoter-proximal pausing and increases RNAP elongation when uncoupled from translation by depletion of charged tRNAs. DksA has minimal effect on RNAP elongation in vitro and on untranslated RNAs in vivo. In these cases, transcripts can form RNA structures that prevent backtracking. Thus, the effect of DksA on transcript elongation may occur primarily upon ribosome slowing/stalling or at promoter-proximal locations that limit the potential for RNA structure. We propose that inactive ribosomes prevent formation of backtrack-blocking mRNA structures and that, in this circumstance, DksA acts as a transcription elongation factor in vivo.

A unified model of transcription elongation: what have we learned from single-molecule experiments?

The transcription of the genetic information encoded in DNA into RNA is performed by RNA polymerase (RNAP), a complex molecular motor, highly conserved across species. Despite remarkable progress in single-molecule techniques revealing important mechanistic details of transcription elongation (TE) with up to base-pair resolution, some of the results and interpretations of these studies are difficult to reconcile, and have not yet led to a minimal unified picture of transcription. We propose a simple model that accounts quantitatively for many of the experimental observations. This model belongs to the class of isothermal ratchet models of TE involving the thermally driven stochastic backward and forward motion (backtracking and forward tracking) of RNAP along DNA between single-nucleotide incorporation events. We uncover two essential features for the success of the model. The first is an intermediate state separating the productive elongation pathway from nonelongating backtracked states. The rates of entering and exiting this intermediate state modulate pausing by RNAP. The second crucial ingredient of the model is the cotranscriptional folding of the RNA transcript, sterically inhibiting the extent of backtracking. This model resolves several apparent differences between single-molecule studies and provides a framework for future work on TE.

Pause locally, splice globally

Most eukaryotic protein-coding transcripts contain introns, which vary in number and position along the transcript body. Intron removal through pre-mRNA splicing is tightly linked to transcription by RNA polymerase II as it translocates along each gene. Here, we review recent evidence that transcription and splicing are functionally coupled. We focus on how RNA polymerase II elongation rates impact splicing through local regulation and transcriptional pausing within genes. Emerging concepts of how splicing-related changes in elongation might be achieved are highlighted. We place the interplay between transcription and splicing in the context of chromatin where nucleosome positioning influences elongation, and histone modifications participate directly in the recruitment of splicing regulators to nascent transcripts.

A sequential folding model predicts length-independent secondary structure properties of long ssRNA

We introduce a simple model for folding random-sequence RNA molecules, arguing that it provides a direct route to predicting and rationalizing several average properties of RNA secondary structures. The first folding step involves identifying the longest possible duplex, thereby dividing the molecule into a pair of daughter loops. Successive steps involve identifying similarly the longest duplex in each new pair of daughter loops, with this process proceeding sequentially until the loops are too small for a viable duplex to form. Approximate analytical solutions are found for the average fraction of paired bases, the average duplex length, and the average loop size, all of which are shown to be independent of sequence length for long enough molecules. Numerical solutions to the model provide estimates for these average secondary structure properties that agree well with those obtained from more sophisticated folding algorithms. We also use the model to derive the asymptotic power law for the dependence of the maximum ladder distance on chain length.

GC content around splice sites affects splicing through pre-mRNA secondary structures

Background

Alternative splicing increases protein diversity by generating multiple transcript isoforms from a single gene through different combinations of exons or through different selections of splice sites. It has been reported that RNA secondary structures are involved in alternative splicing. Here we perform a genomic study of RNA secondary structures around splice sites in humans (Homo sapiens), mice (Mus musculus), fruit flies (Drosophila melanogaster), and nematodes (Caenorhabditis elegans) to further investigate this phenomenon.

Results

We observe that GC content around splice sites is closely associated with the splice site usage in multiple species. RNA secondary structure is the possible explanation, because the structural stability difference among alternative splice sites, constitutive splice sites, and skipped splice sites can be explained by the GC content difference. Alternative splice sites tend to be GC-enriched and exhibit more stable RNA secondary structures in all of the considered species. In humans and mice, splice sites of first exons and long exons tend to be GC-enriched and hence form more stable structures, indicating the special role of RNA secondary structures in promoter proximal splicing events and the splicing of long exons. In addition, GC-enriched exon-intron junctions tend to be overrepresented in tissue-specific alternative splice sites, indicating the functional consequence of the GC effect. Compared with regions far from splice sites and decoy splice sites, real splice sites are GC-enriched. We also found that the GC-content effect is much stronger than the nucleotide-order effect to form stable secondary structures.

Conclusion

All of these results indicate that GC content is related to splice site usage and it may mediate the splicing process through RNA secondary structures.