Literature DB >> 1787735

A stochastic model for gene induction.

M S Ko1.   

Abstract

Expression levels of individual copies of an inducible gene have been presumed to be identical to the averaged level of many copies and to change in a smooth and predictable way according to the concentration of an inducing molecule. However, our recent experiments using a steroid-inducible system showed that the expression levels of individual copies are very heterogeneous and do not necessarily coincide with the averaged expression level of many copies (Ko et al., 1990, EMBO J. 9, 2835-2842). To explain this result, I present a stochastic model for gene induction here and its analysis using computer simulation. Stochasticity in the model is derived from the randomness corresponding to the random timing of molecular collisions and dissociations between transcription factors and a gene copy, since at any instant each copy is thought to be either "switched on" by having a transcription complex bound to it, or "switched off" by not having a transcription complex bound. This model can produce two types of gene induction that depend on the stability of the transcription complex on the regulatory region of the gene. An unstable transcription complex causes a homogeneous level of gene induction among individual copies, while a stable transcription complex causes a heterogeneous level. Since the recent consensus formed by in vitro transcription experiments is that the transcription complex is generally very stable, the latter case (the non-deterministic one) is highly possible. Since typical eukaryotic cells have just two copies for any gene in a single cell, this possibility of heterogeneous gene induction indicates that the phenotypes of individual cells cannot be precisely determined by just environmental signals, such as inducers. This may prompt us to reconsider many problems related to gene induction, including morphogenesis.

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Year:  1991        PMID: 1787735     DOI: 10.1016/s0022-5193(05)80421-7

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  51 in total

1.  Stochasticity in transcriptional regulation: origins, consequences, and mathematical representations.

Authors:  T B Kepler; T C Elston
Journal:  Biophys J       Date:  2001-12       Impact factor: 4.033

2.  Intrinsic noise in gene regulatory networks.

Authors:  M Thattai; A van Oudenaarden
Journal:  Proc Natl Acad Sci U S A       Date:  2001-07-03       Impact factor: 11.205

3.  Intrinsic and extrinsic contributions to stochasticity in gene expression.

Authors:  Peter S Swain; Michael B Elowitz; Eric D Siggia
Journal:  Proc Natl Acad Sci U S A       Date:  2002-09-17       Impact factor: 11.205

4.  Control of stochasticity in eukaryotic gene expression.

Authors:  Jonathan M Raser; Erin K O'Shea
Journal:  Science       Date:  2004-05-27       Impact factor: 47.728

5.  Stochastic simulation of the mammalian circadian clock.

Authors:  Daniel B Forger; Charles S Peskin
Journal:  Proc Natl Acad Sci U S A       Date:  2004-12-30       Impact factor: 11.205

Review 6.  Noise in gene expression: origins, consequences, and control.

Authors:  Jonathan M Raser; Erin K O'Shea
Journal:  Science       Date:  2005-09-23       Impact factor: 47.728

7.  Diffusion of transcription factors can drastically enhance the noise in gene expression.

Authors:  Jeroen S van Zon; Marco J Morelli; Sorin Tănase-Nicola; Pieter Rein ten Wolde
Journal:  Biophys J       Date:  2006-09-29       Impact factor: 4.033

8.  Modeling stochastic gene expression under repression.

Authors:  G C P Innocentini; J E M Hornos
Journal:  J Math Biol       Date:  2007-05-22       Impact factor: 2.259

Review 9.  Determining biological noise via single cell analysis.

Authors:  Edgar A Arriaga
Journal:  Anal Bioanal Chem       Date:  2008-10-29       Impact factor: 4.142

Review 10.  Nature, nurture, or chance: stochastic gene expression and its consequences.

Authors:  Arjun Raj; Alexander van Oudenaarden
Journal:  Cell       Date:  2008-10-17       Impact factor: 41.582

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