Stochastic modeling for the expression of a gene regulated by competing transcription factors

Hsih Te Yang, Minoru Ko

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

It is widely accepted that gene expression regulation is a stochastic event. The common approach for its computer simulation requires detailed information on the interactions of individual molecules, which is often not available for the analyses of biological experiments. As an alternative approach, we employed a more intuitive model to simulate the experimental result, the Markov-chain model, in which a gene is regulated by activators and repressors, which bind the same site in a mutually exclusive manner. Our stochastic simulation in the presence of both activators and repressors predicted a Hill-coefficient of the dose-response curve closer to the experimentally observed value than the calculated value based on the simple additive effects of activators alone and repressors alone. The simulation also reproduced the heterogeneity of gene expression levels among individual cells observed by Fluorescence Activated Cell Sorting analysis. Therefore, our approach may help to apply stochastic simulations to broader experimental data.

Original languageEnglish
Article numbere32376
JournalPLoS One
Volume7
Issue number3
DOIs
Publication statusPublished - 2012 Mar 14
Externally publishedYes

Fingerprint

Markov Chains
Gene Expression Regulation
Computer Simulation
Gene expression regulation
Flow Cytometry
Transcription Factors
transcription factors
Genes
Gene Expression
gene expression
gene expression regulation
additive effect
Sorting
computer simulation
Gene expression
Markov processes
dose response
flow cytometry
Fluorescence
Cells

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Stochastic modeling for the expression of a gene regulated by competing transcription factors. / Yang, Hsih Te; Ko, Minoru.

In: PLoS One, Vol. 7, No. 3, e32376, 14.03.2012.

Research output: Contribution to journalArticle

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