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Transcriptional stochasticity in gene expression

Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcrip...

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Bibliographische Detailangaben
Hauptverfasser: Lipniacki, Tomasz (VerfasserIn) , Marciniak-Czochra, Anna (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 2006
In: Journal of theoretical biology
Year: 2005, Jahrgang: 238, Heft: 2, Pages: 348-367
ISSN:1095-8541
DOI:10.1016/j.jtbi.2005.05.032
Online-Zugang:Resolving-System, Volltext: http://dx.doi.org/10.1016/j.jtbi.2005.05.032
Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S002251930500250X
Volltext
Verfasserangaben:Tomasz Lipniacki, Pawel Paszek, Anna Marciniak-Czochra, Allan R. Brasier, Marek Kimmel

MARC

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520 |a Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcription factor binding to a specific regulatory site in the target gene. Stochasticity of transcription factor binding and dissociation is then amplified by transcription and translation, since target gene activation results in a burst of mRNA molecules, and each mRNA copy serves as a template for translating numerous protein molecules. In the present paper, we explore a mathematical approach to stochastic modeling. In this approach, the ordinary differential equations with a stochastic component for mRNA and protein levels in a single cells yield a system of first-order partial differential equations (PDEs) for two-dimensional probability density functions (pdf). We consider the following examples: Regulation of a single auto-repressing gene, and regulation of a system of two mutual repressors and of an activator-repressor system. The resulting PDEs are approximated by a system of many ordinary equations, which are then numerically solved. 
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