scholarly journals Kinetic characteristics of transcriptional bursting in a complex gene model with cyclic promoter structure

2021 ◽  
Author(s):  
Xiyan Yang ◽  
Zihao Wang ◽  
Yahao Wu ◽  
Tianshou Zhou ◽  
Jiajun Zhang
Keyword(s):  
Experimental Data ◽  
Geometric Distribution ◽  
Burst Size ◽  
Mrna Expression Level ◽  
Kinetic Characteristics ◽  
Exponential Distributions ◽  
Gene Model ◽  
Promoter Structure ◽  
Transcriptional Bursting ◽  
Cell To Cell Variability

While transcription occurs often in a bursty manner, various possible regulations can lead to complex promoter patterns such as promoter cycles, giving rise to an important issue: How do promoter kinetics shape transcriptional bursting kinetics? Here we introduce and analyze a general model of the promoter cycle consisting of multi-OFF states and multi-ON states, focusing on the effects of multi-ON mechanisms on transcriptional bursting kinetics. The derived analytical results indicate that bust size follows a mixed geometric distribution rather than a single geometric distribution assumed in previous studies, and ON and OFF times obey their own mixed exponential distributions. In addition, we find that the multi-ON mechanism can lead to bimodal burst-size distribution, antagonistic timing of ON and OFF, and diverse burst frequencies, each further contributing to cell-to-cell variability in the mRNA expression level. These results not only reveal essential features of transcriptional bursting kinetics patterns shaped by multi-state mechanisms but also can be used to the inferences of transcriptional bursting kinetics and promoter structure based on experimental data.

The Kinetics of Austenization Process of T91 Ferritic Heat-Resistant Steel

2011 ◽  
Vol 317-319 ◽  
pp. 42-47
Author(s):  
Li Fang Zhang ◽  
Yong Chang Liu
Keyword(s):  
Experimental Data ◽  
Phase Transformation ◽  
Kinetic Parameters ◽  
Nucleation And Growth ◽  
Transformation Model ◽  
Resistant Steel ◽  
Kinetic Characteristics ◽  
Heat Resistant Steel ◽  
Austenite Grain ◽  
Kinetics Of

By fitting the calculated transformed fraction according to developed phase-transformation model to the experimental data obtained by differential dilatometry, the kinetic characteristics of the austenitization process in T91 steels have been investigated. According to the kinetic parameters fitted, we recognize that the nucleation and growth of austenite grain are mainly controlled by the diffusion of carbon in ferritic and austenite respectively. In addition, by increasing the diffusion active energy of carbon in austenite, carbides hinder the motion of interface and thus refine austenite grain.

scholarly journals Transcriptional bursting explains the noise-versus-mean relationship in mRNA and protein levels

2016 ◽  
Author(s):  
Roy D. Dar ◽  
Sydney M. Schaffer ◽  
Siddarth S. Dey ◽  
Jonathan E. Foley ◽  
Abhyudai Singh ◽  
...  
Keyword(s):  
Conflict Of Interest ◽  
Burst Size ◽  
Inverse Correlation ◽  
Recent Analysis ◽  
Mrna Levels ◽  
Burst Frequency ◽  
Expression Variability ◽  
Protein Levels ◽  
Transcriptional Bursting ◽  
Cell Expression

Recent analysis (Dey et al, 2015), demonstrates that the HIV-1 Long Terminal Repeat (HIV LTR) promoter exhibits a range of possible transcriptional burst sizes and frequencies for any mean-expression level. However, these results have also been interpreted as demonstrating that cell-to-cell expression variability (noise) and mean are uncorrelated, a significant deviation from previous results. Here, we re-examine the available mRNA and protein abundance data for the HIV LTR and find that noise in mRNA and protein expression scales inversely with the mean along analytically predicted transcriptional burst-size manifolds. We then experimentally perturb transcriptional activity to test a prediction of the multiple burst-size model: that increasing burst frequency will cause mRNA noise to decrease along given burst-size lines as mRNA levels increase. The data show that mRNA and protein noise decrease as mean expression increases, supporting the canonical inverse correlation between noise and mean.Conflict of InterestThe authors declare that they have no conflict of interest.

scholarly journals Three Methods to Calculate the Probability of Ruin

1989 ◽  
Vol 19 (1) ◽  
pp. 71-90 ◽  
Author(s):  
François Dufresne ◽  
Hans U. Gerber
Keyword(s):  
Stationary Distribution ◽  
Geometric Distribution ◽  
Random Variable ◽  
Claim Amount ◽  
Adjustment Coefficient ◽  
Exponential Distributions ◽  
Probability Of Ruin ◽  
The Third ◽  
Compound Geometric Distribution ◽  
Aggregate Loss

AbstractThe first method, essentially due to GOOVAERTS and DE VYLDER, uses the connection between the probability of ruin and the maximal aggregate loss random variable, and the fact that the latter has a compound geometric distribution. For the second method, the claim amount distribution is supposed to be a combination of exponential or translated exponential distributions. Then the probability of ruin can be calculated in a transparent fashion; the main problem is to determine the nontrivial roots of the equation that defines the adjustment coefficient. For the third method one observes that the probability, of ruin is related to the stationary distribution of a certain associated process. Thus it can be determined by a single simulation of the latter. For the second and third methods the assumption of only proper (positive) claims is not needed.

scholarly journals Signaling Mechanism of Transcriptional Bursting: A Technical Resolution-Independent Study

Biology ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 339
Author(s):  
Yaolai Wang ◽  
Jiaming Qi ◽  
Jie Shao ◽  
Xu-Qing Tang
Keyword(s):  
Frequency Modulation ◽  
Transcription Initiation ◽  
Burst Size ◽  
Independent Study ◽  
Transcriptional Activators ◽  
Signaling Mechanism ◽  
Theoretical Predictions ◽  
Support Size ◽  
Analytical Research ◽  
Transcriptional Bursting

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.

scholarly journals Single-molecule imaging reveals the interplay between transcription factors, nucleosomes, and transcriptional bursting

2018 ◽  
Author(s):  
Benjamin T. Donovan ◽  
Anh Huynh ◽  
David A. Ball ◽  
Michael G. Poirier ◽  
Daniel R. Larson ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Single Molecule ◽  
Target Genes ◽  
Burst Size ◽  
Yeast Cells ◽  
Single Molecule Imaging ◽  
Transcriptional Bursting

SummaryTranscription factors show rapid and reversible binding to chromatin in living cells, and transcription occurs in sporadic bursts, but how these phenomena are related is unknown. Using a combination of in vitro and in vivo single-molecule imaging approaches, we directly correlated binding of the transcription factor Gal4 with the transcriptional bursting kinetics of the Gal4 target genes GAL3 and GAL10 in living yeast cells. We find that Gal4 dwell times sets the transcriptional burst size. Gal4 dwell time depends on the affinity of the binding site and is reduced by orders of magnitude by nucleosomes. Using a novel imaging platform, we simultaneously tracked transcription factor binding and transcription at one locus, revealing the timing and correlation between Gal4 binding and transcription. Collectively, our data support a model where multiple polymerases initiate during a burst as long as the transcription factor is bound to DNA, and a burst terminates upon transcription factor dissociation.

scholarly journals OMGene: Mutual improvement of gene models through optimisation of evolutionary conservation

2017 ◽  
Author(s):  
Michael P. Dunne ◽  
Steven Kelly
Keyword(s):  
Experimental Data ◽  
De Novo ◽  
Gene Prediction ◽  
Expression Profiles ◽  
Accurate Determination ◽  
Subcellular Localisation ◽  
Rna Seq ◽  
Gene Model ◽  
Specific Expression ◽  
Gene Models

AbstractBackgroundThe accurate determination of the genomic coordinates for a given gene – its gene model – is of vital importance to the utility of its annotation, and the accuracy of bioinformatic analyses derived from it. Currently-available methods of computational gene prediction, while on the whole successful, often disagree on the model for a given predicted gene, with some or all of the variant gene models failing to match the biologically observed structure. Many prediction methods can be bolstered by using experimental data such as RNA-seq and mass spectrometry. However, these resources are not always available, and rarely give a comprehensive portrait of an organism’s transcriptome due to temporal and tissue-specific expression profiles.ResultsOrthology between genes provides evolutionary evidence to guide the construction of gene models. OMGene (Optimise My Gene) aims to optimise gene models in the absence of experimental data by optimising the derived amino acid alignments for gene models within orthogroups. Using RNA-seq data sets from plants and fungi, considering intron/exon junction representation and exon coverage, and assessing the intra-orthogroup consistency of subcellular localisation predictions, we demonstrate the utility of OMGene for improving gene models in annotated genomes.ConclusionsWe show that significant improvements in the accuracy of gene model annotations can be made in both established and de novo annotated genomes by leveraging information from multiple species.

Dimeric/oligomeric DNA methyltransferases: an unfinished story

2009 ◽  
Vol 390 (9) ◽  
Author(s):  
Ernst G. Malygin ◽  
Alexey A. Evdokimov ◽  
Stanley Hattman
Keyword(s):  
Experimental Data ◽  
Dna Methyltransferases ◽  
Structure And Function ◽  
Type I ◽  
Type Ii ◽  
Kinetic Characteristics ◽  
Biological Substrate ◽  
Oligomeric Dna ◽  
And Function

Abstract DNA methyltransferases (MTases) are enzymes that carry out post-replicative sequence-specific modifications. The initial experimental data on the structure and kinetic characteristics of the EcoRI MTase led to the paradigm that type II systems comprise dimeric endonucleases and monomeric MTases. In retrospect, this was logical because, while the biological substrate of the restriction endonuclease is two-fold symmetrical, the in vivo substrate for the MTase is generally hemi-methylated and, hence, inherently asymmetric. Thus, the paradigm was extended to include all DNA MTases except the more complex bifunctional type I and type III enzymes. Nevertheless, a gradual enlightenment grew over the last decade that has changed the accepted view on the structure of DNA MTases. These results necessitate a more complex view of the structure and function of these important enzymes.

scholarly journals Analysis of experimental data on the kinetic characteristics of milk whey purification using ultrafiltration elements of BTU 05/2 type

2021 ◽  
Vol 82 (4) ◽  
pp. 88-94
Author(s):  
D. A. Rodionov ◽  
S. I. Lazarev ◽  
K. K. Polyansky ◽  
E. V. Eckert ◽  
D. L. Polushkin
Keyword(s):  
Experimental Data ◽  
Distribution Coefficient ◽  
Permeability Coefficient ◽  
Diffusion Permeability ◽  
Kinetic Characteristics ◽  
Membrane Material ◽  
Specific Flow ◽  
Milk Whey ◽  
Retention Coefficient ◽  
Coefficient Distribution

The paper presents the results of experimental data on the kinetic characteristics of ultrafiltration tubular elements, such as the output specific flow, retention coefficient, diffusion permeability coefficient, distribution coefficient. To study the purification of milk whey, we used tubular ultrafilters BTU 05/2 with membrane material fluoroplast (F), polyethersulfone (PESF), polysulfone (PS). For theoretical calculation of the retention coefficient, output specific flux, diffusion permeability coefficient, distribution coefficient, mathematical expressions were developed and empirical coefficients were obtained. The developed mathematical expression describes the experimental data with good reliability. The obtained experimental and calculated data can be used with high reliability in calculating mass-transfer fluxes of substances through a semi-permeable membrane, as well as in engineering methods for calculating and predicting efficiency, and using membrane processes for concentrating serum. The protein concentration in real milk whey was determined by formol titration. On the basis of the studies carried out, the dependence of the growth of the output specific flow on pressure was established, that the optimal pressure for concentrating milk whey on the ultrafiltration membranes we have chosen is 0.25 MPa. For three types of ultrafilters, the experimental value of the coefficient was within 99% for protein. For the theoretical calculation of the retention coefficient, a program in the MAXIMA language was developed and registered. Due to the method of applying the membrane to the reinforcing element, the membrane material polyethersulfone (PESF) and polysulfone (PS) have a substrate, due to which they sorb more substances on themselves, because of this, the diffusion permeability coefficient and the distribution coefficient are much higher than that of a filter element with membrane made of fluoroplastic (F), which does not have a substrate.

scholarly journals The Study of the Correlation between a Specific Output Flow of Acetate Cellulose Films and the Pressure Gradient, Temperature and Classification of the Processes of Membrane Separation of Solutions

2021 ◽  
Vol 27 (1) ◽  
pp. 095-104
Author(s):  
S. I. Lazarev ◽  
◽  
A. A. Arzamastsev ◽  
V. Yu. Ryzhkin ◽  
O. A. Kovaleva ◽  
...  
Keyword(s):  
Experimental Data ◽  
Temperature Effects ◽  
Membrane Separation ◽  
Transmembrane Pressure ◽  
Kinetic Characteristics ◽  
Separation Processes ◽  
Cellulose Films ◽  
Output Flow ◽  
Pressure And Temperature Effects

A comparative study of the application of membrane, electromembrane and electrobaromembrane technologies for various industries in the field of wastewater treatment and technological solutions is presented. The principle of classification of membrane separation processes is formulated. The characteristic periods of the solvent transfer stimulation were determined. Based on the experimental data obtained on the permeability of the solvent through the MGA-80P and MGA-95 membranes, empirical dependences are proposed that describe the kinetic characteristics of the dependence from transmembrane pressure and temperature effects.

scholarly journals Differential context-specific impact of individual core promoter elements on transcriptional dynamics

2017 ◽  
Vol 28 (23) ◽  
pp. 3360-3370 ◽  
Author(s):  
Oliver Hendy ◽  
John Campbell ◽  
Jocelyn D. Weissman ◽  
Daniel R. Larson ◽  
Dinah S. Singer
Keyword(s):  
Mhc Class I ◽  
Core Promoter ◽  
Burst Size ◽  
Promoter Elements ◽  
Transcriptional Dynamics ◽  
Transcriptional Bursting ◽  
Γ Interferon ◽  
I Gene ◽  
Mhc Class I Gene ◽  
Individual Core

Eukaryotic transcription occurs in bursts that vary in size and frequency, but the contribution of individual core promoter elements to transcriptional bursting is not known. Here we analyze the relative contributions to bursting of the individual core promoter elements—CCAAT, TATAA-like, Sp1BS, and Inr—of an MHC class I gene in primary B-cells during both basal and activated transcription. The TATAA-like, Sp1BS, and Inr elements all function as negative regulators of transcription, and each was found to contribute differentially to the overall bursting pattern of the promoter during basal transcription. Whereas the Sp1BS element regulates burst size, the Inr element regulates burst frequency. The TATAA-like element contributes to both. Surprisingly, each element has a distinct role in bursting during transcriptional activation by γ-interferon. The CCAAT element does not contribute significantly to the constitutive transcriptional dynamics of primary B-cells, but modulates both burst size and frequency in response to γ-interferon activation. The ability of core promoter elements to modulate transcriptional bursting individually allows combinatorial fine-tuning of the level of MHC class I gene expression in response to intrinsic and extrinsic signals.

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