ArticleNucleic acids research2023
BurstDECONV: a signal deconvolution method to uncover mechanisms of transcriptional bursting in live cells.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Cell heterogeneity contributes to the variable response of HIV-1 to latency-reversing agents.Science advances · 2026Article
- Transcriptional Bursting in Pluripotent Stem Cells.Biology · 2026Review
- Mitotic reactivation and transcriptional bursting govern transcriptional noise in the early Drosophila embryo.Development (Cambridge, England) · 2026Article
- A single cluster of RNA Polymerase II molecules is stably associated with active genes.Nature communications · 2026Article
- Direct observation of Notch signaling-induced transcription hubs mediating gene-expression responses.Science advances · 2026Article
- A single cluster of RNA Polymerase II molecules is stably associated with active genes.bioRxiv : the preprint server for biology · 2025Article
- Timing is everything: transcription bursting in development.Genes & development · 2025Review
- Coordinated active repression operates via transcription factor cooperativity and multiple inactive promoter states in a developing organism.Nature communications · 2025Article
- Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression.Nature communications · 2025Article
- Optogenetic manipulation of nuclear Dorsal reveals temporal requirements and consequences for transcription.Development (Cambridge, England) · 2025Article
- Two-State Stochastic Model of In Vivo Observations of Transcriptional Bursts.Brazilian journal of physics · 2025Article
- Deciphering HIV-1 Transcription Initiation and Elongation from Single-Molecule Imaging Data.Research (Washington, D.C.) · 2025Article
- Optogenetic manipulation of nuclear Dorsal reveals temporal requirements and consequences for transcription.bioRxiv : the preprint server for biology · 2024Article
- Solving stochastic gene-expression models using queueing theory: A tutorial review.Biophysical journal · 2024Review
- Time will tell: comparing timescales to gain insight into transcriptional bursting.Trends in genetics : TIG · 2024Review
- Review
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5 authors.
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Abstract
Monitoring transcription in living cells gives access to the dynamics of this complex fundamental process. It reveals that transcription is discontinuous, whereby active periods (bursts) are separated by one or several types of inactive periods of distinct lifetimes. However, decoding temporal fluctuations arising from live imaging and inferring the distinct transcriptional steps eliciting them is a challenge. We present BurstDECONV, a novel statistical inference method that deconvolves signal traces into individual transcription initiation events. We use the distribution of waiting times between successive polymerase initiation events to identify mechanistic features of transcription such as the number of rate-limiting steps and their kinetics. Comparison of our method to alternative methods emphasizes its advantages in terms of precision and flexibility. Unique features such as the direct determination of the number of promoter states and the simultaneous analysis of several potential transcription models make BurstDECONV an ideal analytic framework for live cell transcription imaging experiments. Using simulated realistic data, we found that our method is robust with regards to noise or suboptimal experimental designs. To show its generality, we applied it to different biological contexts such as Drosophila embryos or human cells.
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