RNA–DNA and DNA–DNA base-pairing at the upstream edge of the transcription bubble regulate translocation of RNA polymerase and transcription rate

Kireeva, Maria L.; Trang, Cyndi; Matevosyan, Gayane; Turek-Herman, Joshua; Chasov, Vitaly; Lubkowska, Lucyna; Kashlev, Mikhail

doi:10.1093/nar/gky393

“…Thus, for all three polymerases, K τ < 1, indicating that the small energetic preference that the protein has for the posttranslocated state is sufficient to override the loss of basepairing energy, thereby biasing the system towards population of the posttranslocated positions. This is in agreement with estimates made for pol II and T7 pol [26,27,35,36,41] and Kireeva et al 2018 [58] for RNAP: "forward translocation occurs in milliseconds and is poorly reversible". However these estimates are inconsistent with some RNAP and pol II studies which place this ratio above 1 [4,17,42,52].…”

Section: Rnap Has An Energetic Preference For the Posttranslocated Statesupporting

confidence: 91%

“…For RNAP and pol II, translocation has frequently been modelled as an equilibrium process [4,21,26,41,43], however in some recent analyses this assumption has been rejected [16,17,42,57,58]. Our Bayesian analysis supports this.…”

Section: Dg Z T (K B T)supporting

confidence: 65%

Bayesian inference and comparison of stochastic transcription elongation models

Douglas

¹

,

Kingston

²

,

Drummond

³

2020

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Transcription elongation can be modelled as a three step process, involving polymerase translocation, NTP binding, and nucleotide incorporation into the nascent mRNA. This cycle of events can be simulated at the single-molecule level as a continuous-time Markov process using parameters derived from single-molecule experiments. Previously developed models differ in the way they are parameterised, and in their incorporation of partial equilibrium approximations. We have formulated a hierarchical network comprised of 12 sequence-dependent transcription elongation models. The simplest model has two parameters and assumes that both translocation and NTP binding can be modelled as equilibrium processes. The most complex model has six parameters makes no partial equilibrium assumptions. We systematically compared the ability of these models to explain published force-velocity data, using approximate Bayesian computation. This analysis was performed using data for the RNA polymerase complexes of E. coli, S. cerevisiae and Bacteriophage T7. Our analysis indicates that the polymerases differ significantly in their translocation rates, with the rates in T7 pol being fast compared to E. coli RNAP and S. cerevisiae pol II. Different models are applicable in different cases. We also show that all three RNA polymerases have an energetic preference for the posttranslocated state over the pretranslocated state. A Bayesian inference and model selection framework, like the one presented in this publication, should be routinely applicable to the interrogation of single-molecule datasets.

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“…Thus, for all three polymerases, the small energetic preference that the protein has 352 for the posttranslocated state is sufficient to override the loss of basepairing energy, 353 thereby biasing the system towards population of the posttranslocated positions. This is 354 in agreement with some estimates for T7 pol and pol II which place K τ less than 355 1 [27,28,33,34,39] and KIreeva et al 2018 [43]: "forward translocation occurs in 356 milliseconds and is poorly reversible". However these estimates are inconsistent with 357 some RNAP and pol II studies which place this ratio above 1 [6,21,35].…”

supporting

confidence: 83%

“…For RNAP and pol II, translocation has frequently been modelled as an equilibrium 306 process [6,22,27,39,41], however in some recent analyses this assumption has been 307 rejected [21,23,35,42,43]. Our Bayesian analysis supports this.…”

supporting

confidence: 52%

Bayesian inference and comparison of stochastic transcription elongation models

Douglas

¹

,

Kingston

²

,

Drummond

³

2018

Preprint

1

0

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Transcription elongation can be modelled as a three step process, involving polymerase translocation, NTP binding, and nucleotide incorporation into the nascent mRNA. This cycle of events can be simulated at the single-molecule level as a continuous-time Markov process using parameters derived from single-molecule experiments. Previously developed models differ in the way they are parameterised, and in their incorporation of partial equilibrium approximations.We have formulated a hierarchical network comprised of 12 sequence-dependent transcription elongation models. The simplest model has two parameters and assumes that both translocation and NTP binding can be modelled as equilibrium processes. The most complex model has six parameters makes no partial equilibrium assumptions. We systematically compared the ability of these models to explain published force-velocity data, using approximate Bayesian computation. This analysis was performed using data for the RNA polymerases of E. coli, S. cerevisiae and Bacteriophage T7.Our analysis indicates that the polymerases differ significantly in their translocation rates, with the rates in T7 pol being fast compared to E. coli RNAP and S. cerevisiae pol II. Different models are applicable in different cases. We also show that all three RNA polymerases have an energetic preference for the posttranslocated state over the pretranslocated state. A Bayesian inference and model selection framework, like the one presented in this publication, should be routinely applicable to the interrogation of single-molecule datasets. Author summaryTranscription is a critical biological process which occurs in all living organisms. It involves copying the organism's genetic material into messenger RNA (mRNA) which directs protein synthesis on the ribosome. Transcription is performed by RNA polymerases which have been extensively studied using both ensemble and single-molecule techniques (see reviews: [1,2]). Single-molecule data provides unique insights into the molecular behaviour of RNA polymerase. Transcription at the single-molecule level can be computationally simulated as a continuous-time Markov process and the model outputs compared with experimental data. In this study we use Bayesian techniques to perform a systematic comparison of 12 stochastic models of transcriptional elongation. We demonstrate how equilibrium approximations can strengthen or weaken the model, and show how Bayesian techniques can identify December 12, 2018 1/23 Introduction 1 Transcription is carried out by RNA polymerases: RNAP in Escherichia coli, pol II in 2 Saccharomyces cerevisiae, and T7 pol in Bacteriophage T7. It involves the copying of 3 template double-stranded DNA (dsDNA) into single-stranded messenger RNA (mRNA). 4The template is read in the 3 to 5 direction, while the mRNA is extended sequentially 5 in the 5 to 3 direction. RNAP and pol II are comprised of multiple subunits, and their 6 catalytic subunits are homologous [3,4]. In contrast, T7 pol exists as a monomer with a 7 distinct sequence, and ...

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“…In support of this hypothesis, the lid appears to have pronounced effects on forward translocation of RNAP adjacent to a terminator hairpin [51]. Based on these observations, we speculate that restricting lid mobility with disulfide crosslinks may destabilize the upstream forkjunction because lid mobility stabilizes the hybrid as it shifts translocation register.…”

Section: Upstream Fork-junction Mobility May Weaken Terminators That mentioning

confidence: 52%

RNA polymerase clamp movement aids dissociation from DNA but is not required for RNA release at intrinsic terminators

Bellecourt

¹

,

Ray-Soni

²

,

Harwig

³

et al. 2018

Preprint

0

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Highlights• Disulfide bond crosslinks probe the role of the RNAP clamp domain in termination • RNA but not DNA can release at terminators when the RNAP clamp is closed • Restricting RNAP clamp movement affects elongation rate more than termination rate • Inhibiting TL conformational flexibility impairs both RNA and DNA release ABSTRACTIn bacteria, disassembly of elongating transcription complexes (ECs) can occur at intrinsic terminators in a 2-3 nucleotide window after transcription of multiple kilobase pairs of DNA. Intrinsic terminators trigger pausing on weak RNA-DNA hybrids followed by formation of a strong, GC-rich stem-loop in the RNA exit channel of RNA polymerase (RNAP), inactivating nucleotide addition and inducing dissociation of RNA and RNAP from DNA. Although the movements of RNA and DNA during intrinsic termination have been studied extensively leading to multiple models, the effects of RNAP conformational changes remain less well-defined. RNAP contains a clamp domain that closes around the nucleic-acid scaffold during transcription initiation and can be displaced by either swiveling or opening motions. Clamp opening is proposed to promote termination by releasing RNAP-nucleic acid contacts. We developed a cysteine-crosslinking assay to constrain clamp movements and study effects on intrinsic termination. We found that biasing the clamp into different conformations perturbed termination efficiency, but that perturbations were due primarily to changes in elongation rate, not the competing rate at which ECs commit to termination. After commitment, however, inhibiting clamp movements slowed release of DNA but not of RNA from the EC. We also found that restricting trigger-loop movements with the RNAP inhibitor microcin J25 prior to commitment inhibits termination, in agreement with a recently proposed multistate-multipath model of intrinsic termination. Together our results support views that termination commitment and DNA release are separate steps and that RNAP may remain associated with DNA after termination.

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RNA–DNA and DNA–DNA base-pairing at the upstream edge of the transcription bubble regulate translocation of RNA polymerase and transcription rate

Cited by 16 publications

References 57 publications

Bayesian inference and comparison of stochastic transcription elongation models

Bayesian inference and comparison of stochastic transcription elongation models

Bayesian inference and comparison of stochastic transcription elongation models

RNA polymerase clamp movement aids dissociation from DNA but is not required for RNA release at intrinsic terminators

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