Unknown

Dataset Information

0

Effect of promoter architecture on the cell-to-cell variability in gene expression.


ABSTRACT: According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article we make such a systematic investigation, based on a microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous) and how each of these affects the level of variability in transcriptional output from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can be used to test kinetic models of gene regulation. The emphasis of the discussion is on prokaryotic gene regulation, but our analysis can be extended to eukaryotic cells as well.

SUBMITTER: Sanchez A 

PROVIDER: S-EPMC3048382 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

altmetric image

Publications

Effect of promoter architecture on the cell-to-cell variability in gene expression.

Sanchez Alvaro A   Garcia Hernan G HG   Jones Daniel D   Phillips Rob R   Kondev Jané J  

PLoS computational biology 20110303 3


According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article w  ...[more]

Similar Datasets

| S-EPMC4388425 | biostudies-literature
| S-EPMC9844987 | biostudies-literature
| S-EPMC5068849 | biostudies-literature
| S-EPMC4859557 | biostudies-literature
| S-EPMC3044413 | biostudies-other
2022-11-14 | GSE188131 | GEO
2022-11-14 | GSE188130 | GEO
2022-11-14 | GSE188099 | GEO
| S-EPMC7959723 | biostudies-literature
| S-EPMC3659125 | biostudies-literature