ArticleMolecular systems biology2015
Structure of silent transcription intervals and noise characteristics of mammalian genes.
Article in Molecular systems biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
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Who cites it
71 citing papers in PubMed.
- Stable epigenetic states set single-cell activation thresholds in mammalian expression systems.bioRxiv : the preprint server for biology · 2026Article
- Invariant nonequilibrium dynamics in gene regulation optimize information flow.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Heritable single-cell gene expression states shape functional variability in innate immune responses.bioRxiv : the preprint server for biology · 2026Article
- Review
- Mitotic reactivation and transcriptional bursting govern transcriptional noise in the early Drosophila embryo.Development (Cambridge, England) · 2026Article
- Epigenetics, Modifiers, and Molecular Noise: Rethinking Pathophysiology in Dilated and Hypertrophic Cardiomyopathies.International journal of molecular sciences · 2026Review
- Article
- Assessment of dispersion metrics for estimating single-cell transcriptional variability.PLoS computational biology · 2026Article
- From noise to models to numbers: Evaluating negative binomial models and parameter estimations in single-cell RNA-seq.PLoS computational biology · 2026Article
- Antisense transcription can induce expression memory via stable promoter repression.Genome biology · 2025Article
- A conserved coupling of transcriptional ON and OFF periods underlies bursting dynamics.Nature structural & molecular biology · 2025Article
- Mouse promoters are characterised by low occupancy and high turnover of RNA polymerase II.Molecular systems biology · 2025Article
- Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression.Nature communications · 2025Article
- What can we learn when fitting a simple telegraph model to a complex gene expression model?PLoS computational biology · 2024Article
- Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Quantifying and correcting bias in transcriptional parameter inference from single-cell data.Biophysical journal · 2024Article
- Transcriptional bursting dynamics in gene expression.Frontiers in genetics · 2024Review
- Article
- LAST-seq: single-cell RNA sequencing by direct amplification of single-stranded RNA without prior reverse transcription and second-strand synthesis.Genome biology · 2023Article
- Transcriptional bursting: stochasticity in deterministic development.Development (Cambridge, England) · 2023Review
11 more citing papers are in PubMed but not listed here.
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Mammalian transcription occurs stochastically in short bursts interspersed by silent intervals showing a refractory period. However, the underlying processes and consequences on fluctuations in gene products are poorly understood. Here, we use single allele time-lapse recordings in mouse cells to identify minimal models of promoter cycles, which inform on the number and durations of rate-limiting steps responsible for refractory periods. The structure of promoter cycles is gene specific and independent of genomic location. Typically, five rate-limiting steps underlie the silent periods of endogenous promoters, while minimal synthetic promoters exhibit only one. Strikingly, endogenous or synthetic promoters with TATA boxes show simplified two-state promoter cycles. Since transcriptional bursting constrains intrinsic noise depending on the number of promoter steps, this explains why TATA box genes display increased intrinsic noise genome-wide in mammals, as revealed by single-cell RNA-seq. These findings have implications for basic transcription biology and shed light on interpreting single-cell RNA-counting experiments.
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