ArticlePLoS computational biology2011
Effect of promoter architecture on the cell-to-cell variability in gene expression.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.
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Who cites it
80 citing papers in PubMed.
- Impact of variability in cell generation times on cell-to-cell variability of protein concentrations.bioRxiv : the preprint server for biology · 2026Article
- Beyond the mean: genetic control of gene expression fidelity and dispersion.bioRxiv : the preprint server for biology · 2026Article
- How cells tame noise while maintaining ultrasensitive transcriptional responses.PLoS computational biology · 2025Article
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- Cyclo-stationary distributions of mRNA and Protein counts for random cell division times.bioRxiv : the preprint server for biology · 2025Article
- Anti-correlation of LacI association and dissociation rates observed in living cells.Nature communications · 2025Article
- From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation.Computational and structural biotechnology journal · 2025Article
- Article
- Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.PLoS computational biology · 2024Article
- Interpretable prediction of mRNA abundance from promoter sequence using contextual regression models.NAR genomics and bioinformatics · 2024Article
- Governing principles of transcriptional logic out of equilibrium.Biophysical journal · 2024Article
- Plasmid-mediated phenotypic noise leads to transient antibiotic resistance in bacteria.Nature communications · 2024Article
- A robust ultrasensitive transcriptional switch in noisy cellular environments.NPJ systems biology and applications · 2024Article
- Effects of microRNA-mediated negative feedback on gene expression noise.Biophysical journal · 2023Article
- Metabolic engineering ofMicrobiology spectrum · 2023Article
- BurstDECONV: a signal deconvolution method to uncover mechanisms of transcriptional bursting in live cells.Nucleic acids research · 2023Article
- Genome-wide inference reveals that feedback regulations constrain promoter-dependent transcriptional burst kinetics.Nucleic acids research · 2023Article
- Genome-Wide Analysis of Gene Expression Noise Brought About by Transcriptional Regulation inmSystems · 2022Article
- Transcription factor binding process is the primary driver of noise in gene expression.PLoS genetics · 2022Article
- Controlling gene expression timing through gene regulatory architecture.PLoS computational biology · 2022Article
20 more citing papers are in PubMed but not listed here.
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5 authors.
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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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.