ArticleMolecular systems biology2010
Transcript counting in single cells reveals dynamics of rDNA transcription.
Article in Molecular systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed, 51 citations in OpenAlex.
- Article
- Non-coding antisense transcripts: fine regulation of gene expression in cancer.Computational and structural biotechnology journal · 2022Review
- Transcriptional timing and noise of yeast cell cycle regulators-a single cell and single molecule approach.NPJ systems biology and applications · 2018Article
- Inferring extrinsic noise from single-cell gene expression data using approximate Bayesian computation.BMC systems biology · 2016Article
- Viral genome imaging of hepatitis C virus to probe heterogeneous viral infection and responses to antiviral therapies.Virology · 2016Article
- Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.Methods (San Diego, Calif.) · 2015Review
- From analog to digital models of gene regulation.Physical biology · 2015Review
- Aro: a machine learning approach to identifying single molecules and estimating classification error in fluorescence microscopy images.BMC bioinformatics · 2015Article
- Whole-mount single molecule FISH method for zebrafish embryo.Scientific reports · 2015Article
- Modeling bi-modality improves characterization of cell cycle on gene expression in single cells.PLoS computational biology · 2014Article
- Silencing is noisy: population and cell level noise in telomere-adjacent genes is dependent on telomere position and sir2.PLoS genetics · 2014Article
- The cohesin acetyltransferase Eco1 coordinates rDNA replication and transcription.EMBO reports · 2014Article
- Single molecule fluorescence approaches shed light on intracellular RNAs.Chemical reviews · 2014Review
- Cohesion promotes nucleolar structure and function.Molecular biology of the cell · 2014Article
- Patch-clamp recordings and calcium imaging followed by single-cell PCR reveal the developmental profile of 13 genes in iPSC-derived human neurons.Stem cell research · 2014Article
- Analytic approaches to stochastic gene expression in multicellular systems.Biophysical journal · 2013Review
- Ribosome biogenesis in the yeast Saccharomyces cerevisiae.Genetics · 2013Review
- Visualising single molecules of HIV-1 and miRNA nucleic acids.BMC cell biology · 2013Article
- Single-molecule methods for studying gene regulation in vivo.Pflugers Archiv : European journal of physiology · 2013Review
- Single-cell analysis of ribonucleotide reductase transcriptional and translational response to DNA damage.Molecular and cellular biology · 2013Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Most eukaryotes contain many tandem repeats of ribosomal RNA genes of which only a subset is transcribed at any given time. Current biochemical methods allow for the determination of the fraction of transcribing repeats (ON) versus non-transcribing repeats (OFF) but do not provide any dynamical information and obscure any transcription activity at the single-cell level. Here, we use a fluorescence in situ hybridization (FISH) technique that allows the detection of single-RNA molecules in individual yeast cells. We use this method complemented with theoretical modeling to determine the rate of switching from OFF to ON (activation rate) and the average number of RNA molecules produced during each transcriptional burst (burst size). We explore how these two variables change in mutants and different growth conditions, and show that this method resolves changes in these two variables even when the average rDNA expression is unaltered. These phenotypic changes could not have been detected by traditional biochemical assays.
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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.