Literature DB >> 16967259

Stochastic kinetics description of a simple transcription model.

Marc R Roussel1, Rui Zhu.   

Abstract

We study a stochastic model of transcription kinetics in order to characterize the distributions of transcriptional delay and of elongation rates. Transcriptional delay is the time which elapses between the binding of RNA polymerase to a promoter sequence and its dissociation from the DNA template strand with consequent release of the transcript. Transcription elongation is the process by which the RNA polymerase slides along the template strand. The model considers a DNA template strand with one promoter site and n nucleotide sites, and five types of reaction processes, which we think are key ones in transcription. The chemical master equation is a set of ordinary differential equations in 3(n) variables, where n is the number of bases in the template. This model is too huge to be handled if n is large. We manage to get a reduced Markov model which has only 2n independent variables and can well approximate the original dynamics. We obtain a number of analytical and numerical results for this model, including delay and transcript elongation rate distributions. Recent studies of single-RNA polymerase transcription by using optical-trapping techniques raise an issue of whether the elongation rates measured in a population are heterogeneous or not. Our model implies that in the cases studied, different RNA polymerase molecules move at different characteristic rates along the template strand. We also discuss the implications of this work for the mathematical modeling of genetic regulatory circuits.

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Year:  2006        PMID: 16967259     DOI: 10.1007/s11538-005-9048-6

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  10 in total

1.  The Influence of Look-Ahead on the Error Rate of Transcription.

Authors:  Y R Yamada; C S Peskin
Journal:  Math Model Nat Phenom       Date:  2010-01-27       Impact factor: 4.157

2.  Development of a "modular" scheme to describe the kinetics of transcript elongation by RNA polymerase.

Authors:  Sandra J Greive; Jim P Goodarzi; Steven E Weitzel; Peter H von Hippel
Journal:  Biophys J       Date:  2011-09-07       Impact factor: 4.033

3.  A systems view of the protein expression process.

Authors:  Sucheta Gokhale; Dimpal Nyayanit; Chetan Gadgil
Journal:  Syst Synth Biol       Date:  2011-10-19

4.  Fitting experimental transcription data with a comprehensive template-dependent modular kinetic model.

Authors:  Sandra J Greive; Brandon A Dyer; Steven E Weitzel; Jim P Goodarzi; Lisa J Main; Peter H von Hippel
Journal:  Biophys J       Date:  2011-09-07       Impact factor: 4.033

5.  Effects of transcriptional pausing on gene expression dynamics.

Authors:  Tiina Rajala; Antti Häkkinen; Shannon Healy; Olli Yli-Harja; Andre S Ribeiro
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

6.  The origins of time-delay in template biopolymerization processes.

Authors:  Luis Mier-y-Terán-Romero; Mary Silber; Vassily Hatzimanikatis
Journal:  PLoS Comput Biol       Date:  2010-04-01       Impact factor: 4.475

Review 7.  Reconstruction of biochemical networks in microorganisms.

Authors:  Adam M Feist; Markus J Herrgård; Ines Thiele; Jennie L Reed; Bernhard Ø Palsson
Journal:  Nat Rev Microbiol       Date:  2008-12-31       Impact factor: 60.633

8.  Connecting variability in global transcription rate to mitochondrial variability.

Authors:  Ricardo Pires das Neves; Nick S Jones; Lorena Andreu; Rajeev Gupta; Tariq Enver; Francisco J Iborra
Journal:  PLoS Biol       Date:  2010-12-14       Impact factor: 8.029

9.  Mixture distributions in a stochastic gene expression model with delayed feedback: a WKB approximation approach.

Authors:  Pavol Bokes; Alessandro Borri; Pasquale Palumbo; Abhyudai Singh
Journal:  J Math Biol       Date:  2020-06-24       Impact factor: 2.259

10.  TABASCO: A single molecule, base-pair resolved gene expression simulator.

Authors:  Sriram Kosuri; Jason R Kelly; Drew Endy
Journal:  BMC Bioinformatics       Date:  2007-12-19       Impact factor: 3.169

  10 in total

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