7 results on '"Wang, Yaolai"'
Search Results
2. Extracting predictors for lung adenocarcinoma based on Granger causality test and stepwise character selection
- Author
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Fan, Xuemeng, Wang, Yaolai, and Tang, Xu-Qing
- Published
- 2019
- Full Text
- View/download PDF
3. Gene transcription in bursting: a unified mode for realizing accuracy and stochasticity.
- Author
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Wang, Yaolai, Ni, Tengfei, Wang, Wei, and Liu, Feng
- Subjects
- *
GENETIC transcription , *STOCHASTIC analysis , *MESSENGER RNA , *BACTERIA , *CONTINUITY - Abstract
There is accumulating evidence that, from bacteria to mammalian cells, messenger RNAs (mRNAs) are produced in intermittent bursts – a much 'noisier' process than traditionally thought. Based on quantitative measurements at individual promoters, diverse phenomenological models have been proposed for transcriptional bursting. Nevertheless, the underlying molecular mechanisms and significance for cellular signalling remain elusive. Here, we review recent progress, address the above issues and illuminate our viewpoints with simulation results. Despite being widely used in modelling and in interpreting experimental data, the traditional two‐state model is far from adequate to describe or infer the molecular basis and stochastic principles of transcription. In bacteria, DNA supercoiling contributes to the bursting of those genes that express at high levels and are topologically constrained in short loops; moreover, low‐affinity cis‐regulatory elements and unstable protein complexes can play a key role in transcriptional regulation. Integrating data on the architecture, kinetics, and transcriptional input–output function is a promising approach to uncovering the underlying dynamic mechanism. For eukaryotes, distinct bursting features described by the multi‐scale and continuum models coincide with those predicted by four theoretically derived principles that govern how the transcription apparatus operates dynamically. This consistency suggests a unified framework for comprehending bursting dynamics at the level of the structural and kinetic basis of transcription. Moreover, the existing models can be unified by a generic model. Remarkably, transcriptional bursting enables regulatory information to be transmitted in a digital manner, with the burst frequency representing the strength of regulatory signals. Such a mode guarantees high fidelity for precise transcriptional regulation and also provides sufficient randomness for realizing cellular heterogeneity. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
4. Signaling Mechanism of Transcriptional Bursting: A Technical Resolution-Independent Study.
- Author
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Wang, Yaolai, Qi, Jiaming, Shao, Jie, and Tang, Xu-Qing
- Subjects
- *
FORECASTING - Abstract
Simple Summary: Following changing cellular signals, various genes adjust their activities and initiate transcripts with the right rates. The precision of such a transcriptional response has a fundamental role in the survival and development of lives. Quite unexpectedly, gene transcription has been uncovered to occur in sporadic bursts, rather than in a continuous manner. This has raised a provoking issue of how the bursting transmits regulatory signals, and it remains controversial whether the burst size, frequency, or both, take the role of signal transmission. Here, this study showed that only the burst frequency was subject to modulation by activators that carry the regulatory signals. A higher activator concentration led to a larger frequency, whereas the size remains unchanged. When very high, the burst cluster emerged, which may be mistaken as a large burst. This work thus supports the conclusion that transcription regulation is in a "digital" way. Gene transcription has been uncovered to occur in sporadic bursts. However, due to technical difficulties in differentiating individual transcription initiation events, it remains debated as to whether the burst size, frequency, or both are subject to modulation by transcriptional activators. Here, to bypass technical constraints, we addressed this issue by introducing two independent theoretical methods including analytical research based on the classic two-model and information entropy research based on the architecture of transcription apparatus. Both methods connect the signaling mechanism of transcriptional bursting to the characteristics of transcriptional uncertainty (i.e., the differences in transcriptional levels of the same genes that are equally activated). By comparing the theoretical predictions with abundant experimental data collected from published papers, the results exclusively support frequency modulation. To further validate this conclusion, we showed that the data that appeared to support size modulation essentially supported frequency modulation taking into account the existence of burst clusters. This work provides a unified scheme that reconciles the debate on burst signaling. [ABSTRACT FROM AUTHOR]
- Published
- 2020
- Full Text
- View/download PDF
5. Kinetics of transcription initiation directed by multiple cis-regulatory elements on the glnAp2 promoter.
- Author
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Wang Y, Liu F, and Wang W
- Subjects
- Computer Simulation, Entropy, Kinetics, Models, Genetic, Promoter Regions, Genetic, RNA, Messenger biosynthesis, RNA, Messenger genetics, Transcriptional Activation, Gene Expression Regulation, Bacterial, Glutamate-Ammonia Ligase genetics, Transcription Initiation, Genetic
- Abstract
Transcription initiation is orchestrated by dynamic molecular interactions, with kinetic steps difficult to detect. Utilizing a hybrid method, we aim to unravel essential kinetic steps of transcriptional regulation on the glnAp2 promoter, whose regulatory region includes two enhancers (sites I and II) and three low-affinity sequences (sites III-V), to which the transcriptional activator NtrC binds. By structure reconstruction, we analyze all possible organization architectures of the transcription apparatus (TA). The main regulatory mode involves two NtrC hexamers: one at enhancer II transiently associates with site V such that the other at enhancer I can rapidly approach and catalyze the σ
54 -RNA polymerase holoenzyme. We build a kinetic model characterizing essential steps of the TA operation; with the known kinetics of the holoenzyme interacting with DNA, this model enables the kinetics beyond technical detection to be determined by fitting the input-output function of the wild-type promoter. The model further quantitatively reproduces transcriptional activities of various mutated promoters. These results reveal different roles played by two enhancers and interpret why the low-affinity elements conditionally enhance or repress transcription. This work presents an integrated dynamic picture of regulated transcription initiation and suggests an evolutionarily conserved characteristic guaranteeing reliable transcriptional response to regulatory signals., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)- Published
- 2016
- Full Text
- View/download PDF
6. Reconciling the concurrent fast and slow cycling of proteins on gene promoters.
- Author
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Wang Y, Liu F, Li J, and Wang W
- Subjects
- Binding Sites, Chromatin Immunoprecipitation, Stochastic Processes, Models, Genetic, Promoter Regions, Genetic, Transcription, Genetic physiology
- Abstract
During gene transcription, proteins appear to cycle on and off some gene promoters with both long (tens of minutes) and short periods (no more than several minutes). The essence of these phenomena still remains unclear. Here, we propose a stochastic model for the state evolution of promoters in terms of DNA-protein interactions. The model associates the characteristics of microscopic molecular interactions with macroscopic measurable quantities. Through theoretical derivation, we reconcile the contradictory viewpoints on the concurrent fast and slow cycling; both the cycling phenomena are further reproduced by fitting simulation results to the experimental data on the pS2 gene. Our results suggest that the fast cycling dictates how the proteins behave on the promoter and that stable binding hardly occurs. Different kinds of proteins rapidly bind/unbind the promoter at distinct transcriptional stages fulfilling specific functions; this feature is essentially manifested as the slow cycling of proteins when detected by chromatin immunoprecipitation assays. Thus, the slow cycling represents neither stable binding of proteins nor external modulation of the fast cycling. This work also reveals the relationship between the essence and measurement of transcriptional dynamics.
- Published
- 2014
- Full Text
- View/download PDF
7. Dynamic mechanism for the transcription apparatus orchestrating reliable responses to activators.
- Author
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Wang Y, Liu F, and Wang W
- Subjects
- Animals, Enhancer Elements, Genetic genetics, Gene Expression Regulation, Gene Regulatory Networks, Humans, Kinetics, RNA, Messenger genetics, RNA, Messenger metabolism, Algorithms, Models, Genetic, Trans-Activators genetics, Transcription, Genetic genetics
- Abstract
The transcription apparatus (TA) is a huge molecular machine. It detects the time-varying concentrations of transcriptional activators and initiates mRNA transcripts at appropriate rates. Based on the general structural organizations of the TA, we propose how the TA dynamically orchestrates transcriptional responses. The activators rapidly cycle in and out of a clamp-like space temporarily formed between the enhancer and the Mediator, with the concentration of activators encoded as their temporal occupancy rate (R(TOR)) within the space. The entry of activators into this space induces allostery in the Mediator, resulting in a facilitated circumstance for transcriptional reinitiation. The reinitiation rate is much larger than the cycling rate of activators, thereby R(TOR) guiding the amount of transcripts. Based on this mechanism, stochastic simulations can qualitatively reproduce and interpret multiple features of gene expression, e.g., transcriptional bursting is not mere noise as traditionally believed, but rather the basis of reliable transcriptional responses.
- Published
- 2012
- Full Text
- View/download PDF
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