ArticleBMC biology2013
Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.
Article in BMC biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed, 57 citations in OpenAlex.
- From noise to models to numbers: Evaluating negative binomial models and parameter estimations in single-cell RNA-seq.PLoS computational biology · 2026Article
- What makes genes burst.Trends in cell biology · 2026Review
- Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens.Molecular cell · 2025Article
- 3D chromatin architecture, BRD4, and Mediator have distinct roles in regulating genome-wide transcriptional bursting and gene network.Science advances · 2024Article
- Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens.bioRxiv : the preprint server for biology · 2024Article
- Transcriptional bursting dynamics in gene expression.Frontiers in genetics · 2024Review
- Detection of genes with differential expression dispersion unravels the role of autophagy in cancer progression.PLoS computational biology · 2023Article
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- Emerging roles for endogenous retroviruses in immune epigenetic regulation.Immunological reviews · 2022Review
- Forecasting cellular states: from descriptive to predictive biology via single-cell multiomics.Current opinion in systems biology · 2021Article
- Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability.Evolutionary applications · 2021Review
- Identifying chromatin features that regulate gene expression distribution.Scientific reports · 2020Article
- Article
- The Impact of Heterogeneity on Single-Cell Sequencing.Frontiers in genetics · 2019Article
- Imaging transcriptional dynamics.Current opinion in biotechnology · 2018Review
- Splicing heterogeneity: separating signal from noise.Genome biology · 2018Article
- Estrogen-dependent control and cell-to-cell variability of transcriptional bursting.Molecular systems biology · 2018Article
- NF-κB-Chromatin Interactions Drive Diverse Phenotypes by Modulating Transcriptional Noise.Cell reports · 2018Article
- Inferring gene regulatory networks from single-cell data: a mechanistic approach.BMC systems biology · 2017Article
- Integrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.PLoS biology · 2017Article
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundA number of studies have established that stochasticity in gene expression may play an important role in many biological phenomena. This therefore calls for further investigations to identify the molecular mechanisms at stake, in order to understand and manipulate cell-to-cell variability. In this work, we explored the role played by chromatin dynamics in the regulation of stochastic gene expression in higher eukaryotic cells.
resultsFor this purpose, we generated isogenic chicken-cell populations expressing a fluorescent reporter integrated in one copy per clone. Although the clones differed only in the genetic locus at which the reporter was inserted, they showed markedly different fluorescence distributions, revealing different levels of stochastic gene expression. Use of chromatin-modifying agents showed that direct manipulation of chromatin dynamics had a marked effect on the extent of stochastic gene expression. To better understand the molecular mechanism involved in these phenomena, we fitted these data to a two-state model describing the opening/closing process of the chromatin. We found that the differences between clones seemed to be due mainly to the duration of the closed state, and that the agents we used mainly seem to act on the opening probability.
conclusionsIn this study, we report biological experiments combined with computational modeling, highlighting the importance of chromatin dynamics in stochastic gene expression. This work sheds a new light on the mechanisms of gene expression in higher eukaryotic cells, and argues in favor of relatively slow dynamics with long (hours to days) periods of quiet state.
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