ArticleBMC systems biology2010
On the spontaneous stochastic dynamics of a single gene: complexity of the molecular interplay at the promoter.
Article in BMC systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 81 citations in OpenAlex.
- Single-cell transcriptional uncertainty landscape of cell differentiation.F1000Research · 2023Article
- Forecasting cellular states: from descriptive to predictive biology via single-cell multiomics.Current opinion in systems biology · 2021Article
- Automated cell cycle and cell size measurements for single-cell gene expression studies.BMC research notes · 2018Article
- SINCERITIES: inferring gene regulatory networks from time-stamped single cell transcriptional expression profiles.Bioinformatics (Oxford, England) · 2018Article
- Inferring gene regulatory networks from single-cell data: a mechanistic approach.BMC systems biology · 2017Article
- Transcriptional precision and accuracy in development: from measurements to models and mechanisms.Development (Cambridge, England) · 2017Review
- Discrete distributional differential expression (D3E)--a tool for gene expression analysis of single-cell RNA-seq data.BMC bioinformatics · 2016Article
- Temperature-induced variation in gene expression burst size in metazoan cells.BMC molecular biology · 2015Article
- Signal integration by the CYP1A1 promoter--a quantitative study.Nucleic acids research · 2015Article
- Stochastic oscillations induced by intrinsic fluctuations in a self-repressing gene.Biophysical journal · 2014Article
- Reinitiation enhances reliable transcriptional responses in eukaryotes.Journal of the Royal Society, Interface · 2014Article
- Reconciling the concurrent fast and slow cycling of proteins on gene promoters.Journal of the Royal Society, Interface · 2014Article
- Noise and information transmission in promoters with multiple internal States.Biophysical journal · 2014Article
- Promoter-mediated transcriptional dynamics.Biophysical journal · 2014Article
- Can we negotiate with a tumor?PloS one · 2014Article
- Analytic approaches to stochastic gene expression in multicellular systems.Biophysical journal · 2013Review
- Eukaryotic transcriptional dynamics: from single molecules to cell populations.Nature reviews. Genetics · 2013Review
- Systems biophysics of gene expression.Biophysical journal · 2013Review
- Dual gating mechanism and function of P2X7 receptor channels.Biophysical journal · 2013Article
- Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.BMC biology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGene promoters can be in various epigenetic states and undergo interactions with many molecules in a highly transient, probabilistic and combinatorial way, resulting in a complex global dynamics as observed experimentally. However, models of stochastic gene expression commonly consider promoter activity as a two-state on/off system. We consider here a model of single-gene stochastic expression that can represent arbitrary prokaryotic or eukaryotic promoters, based on the combinatorial interplay between molecules and epigenetic factors, including energy-dependent remodeling and enzymatic activities.
resultsWe show that, considering the mere molecular interplay at the promoter, a single-gene can demonstrate an elaborate spontaneous stochastic activity (eg. multi-periodic multi-relaxation dynamics), similar to what is known to occur at the gene-network level. Characterizing this generic model with indicators of dynamic and steady-state properties (including power spectra and distributions), we reveal the potential activity of any promoter and its influence on gene expression. In particular, we can reproduce, based on biologically relevant mechanisms, the strongly periodic patterns of promoter occupancy by transcription factors (TF) and chromatin remodeling as observed experimentally on eukaryotic promoters. Moreover, we link several of its characteristics to properties of the underlying biochemical system. The model can also be used to identify behaviors of interest (eg. stochasticity induced by high TF concentration) on minimal systems and to test their relevance in larger and more realistic systems. We finally show that TF concentrations can regulate many aspects of the stochastic activity with a considerable flexibility and complexity.
conclusionsThis tight promoter-mediated control of stochasticity may constitute a powerful asset for the cell. Remarkably, a strongly periodic activity that demonstrates a complex TF concentration-dependent control is obtained when molecular interactions have typical characteristics observed on eukaryotic promoters (high mobility, functional redundancy, many alternate states/pathways). We also show that this regime results in a direct and indirect energetic cost. Finally, this model can constitute a framework for unifying various experimental approaches. Collectively, our results show that a gene - the basic building block of complex regulatory networks - can itself demonstrate a significantly complex behavior.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.