Stochastic mechanisms in gene expression
Harley H. McAdams,Adam P. Arkin +1 more
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This work has analyzed the chemical reactions controlling transcript initiation and translation termination in a single such "genetically coupled" link as a precursor to modeling networks constructed from many such links.Abstract:
In cellular regulatory networks, genetic activity is controlled by molecular signals that determine when and how often a given gene is transcribed. In genetically controlled pathways, the protein product encoded by one gene often regulates expression of other genes. The time delay, after activation of the first promoter, to reach an effective level to control the next promoter depends on the rate of protein accumulation. We have analyzed the chemical reactions controlling transcript initiation and translation termination in a single such “genetically coupled” link as a precursor to modeling networks constructed from many such links. Simulation of the processes of gene expression shows that proteins are produced from an activated promoter in short bursts of variable numbers of proteins that occur at random time intervals. As a result, there can be large differences in the time between successive events in regulatory cascades across a cell population. In addition, the random pattern of expression of competitive effectors can produce probabilistic outcomes in switching mechanisms that select between alternative regulatory paths. The result can be a partitioning of the cell population into different phenotypes as the cells follow different paths. There are numerous unexplained examples of phenotypic variations in isogenic populations of both prokaryotic and eukaryotic cells that may be the result of these stochastic gene expression mechanisms.read more
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Journal ArticleDOI
Stochastic Gene Expression in a Single Cell
TL;DR: This work constructed strains of Escherichia coli that enable detection of noise and discrimination between the two mechanisms by which it is generated and reveals how low intracellular copy numbers of molecules can fundamentally limit the precision of gene regulation.
Journal ArticleDOI
Core transcriptional regulatory circuitry in human embryonic stem cells.
Laurie A. Boyer,Tong Ihn Lee,Megan F. Cole,Sarah E. Johnstone,Stuart S. Levine,Jacob P. Zucker,Matthew G. Guenther,Roshan M. Kumar,Heather L. Murray,Richard G. Jenner,David K. Gifford,David K. Gifford,David K. Gifford,Douglas A. Melton,Douglas A. Melton,Rudolf Jaenisch,Richard A. Young,Richard A. Young +17 more
TL;DR: Insight is provided into the transcriptional regulation of stem cells and how OCT4, SOX2, and NANOG contribute to pluripotency and self-renewal and how they collaborate to form regulatory circuitry consisting of autoregulatory and feedforward loops.
Journal ArticleDOI
Construction of a genetic toggle switch in Escherichia coli
TL;DR: The construction of a genetic toggle switch is presented—a synthetic, bistable gene-regulatory network—in Escherichia coli and a simple theory is provided that predicts the conditions necessary for bistability.
Journal ArticleDOI
Transcriptional Regulatory Networks in Saccharomyces cerevisiae
Tong Ihn Lee,Nicola J. Rinaldi,François Robert,Duncan T. Odom,Ziv Bar-Joseph,Georg K. Gerber,Nancy M. Hannett,Christopher T. Harbison,Craig M. Thompson,Itamar Simon,Julia Zeitlinger,Ezra G. Jennings,Heather L. Murray,D. Benjamin Gordon,Bing Ren,John J. Wyrick,Jean-Bosco Tagne,Thomas L. Volkert,Ernest Fraenkel,David K. Gifford,Richard A. Young +20 more
TL;DR: This work determines how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells, and identifies network motifs, the simplest units of network architecture, and demonstrates that an automated process can use motifs to assemble a transcriptional regulatory network structure.
Journal ArticleDOI
Modeling and simulation of genetic regulatory systems: a literature review.
TL;DR: This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equation, stochastic equations, and so on.
References
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Journal ArticleDOI
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Madeline A. Shea,Gary K. Ackers +1 more
TL;DR: A quantitative model for processes in the bacteriophage lambda that control the switchover from lysogenic to lytic modes of growth was found capable of predicting essential physiological characteristics of the system over an extended time.