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Genome-wide dynamics of Pol II elongation and its interplay with promoter proximal pausing, chromatin, and exons
Open accessAbstract
Production of mRNA depends critically on the rate of RNA polymerase II (Pol II) elongation. To dissect Pol II dynamics in mouse ES cells, we inhibited Pol II transcription at either initiation or promoter-proximal pause escape with Triptolide or Flavopiridol, and tracked Pol II kinetically using GRO-seq. Both inhibitors block transcription of more than 95% of genes, showing that pause escape, like initiation, is a ubiquitous and crucial step within the transcription cycle. Moreover, paused Pol II is relatively stable, as evidenced from half-life measurements at ∼3200 genes. Finally, tracking the progression of Pol II after drug treatment establishes Pol II elongation rates at over 1000 genes. Notably, Pol II accelerates dramatically while transcribing through genes, but slows at exons. Furthermore, intergenic variance in elongation rates is substantial, and is influenced by a positive effect of H3K79me2 and negative effects of exon density and CG content within genes.
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“Inhibition of P‐TEFb and thus repression of the release of RNA Pol II from promoter‐proximal pausing has been shown to block transcription of almost all genes (Henriques et al, 2013; Jonkers et al, 2014).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“RNA Pol II speed was furthermore also shown to be highly variable within individual genes, as RNA Pol II accelerates while traveling throughout the gene body, starting at 0.5 kb/min in the first 10–15 kb and accelerating up to 2–4 kb/min downstream (Danko et al, 2013; Fuchs et al, 2014b; Jonkers et al, 2014; Saponaro et al, 2014).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In mammals and many other metazoans, promoter‐proximal pausing occurs 25–50 base pairs downstream from the TSS and is a major rate‐limiting step of the transcription cycle (Jonkers et al, 2014; Mayer et al, 2015).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“All these techniques showed in various human cell lines that the average RNA Pol II speed ranges between 1.25 kb/min and 3.5 kb/min (Danko et al, 2013; Fuchs et al, 2014b; Jonkers et al, 2014; Saponaro et al, 2014; Veloso et al, 2014; Liang et al, 2018; Baluapuri et al, 2019; Gregersen et al, 2020).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Although no general correlation has been found between nucleosome occupancy and RNA Pol II speed (Jonkers et al, 2014), nucleosomes bound within exons could nonetheless slow down RNA Pol II transcription.”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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“Moreover, the GC content within gene bodies has been shown to correlate negatively with RNA Pol II speed (Jonkers et al, 2014; Veloso et al, 2014).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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In the citing paper
“Genome‐wide studies have shown that H3K79me2, H2B mono‐ubiquitylation, and H4K20me1 positively correlate with RNA Pol II speed in the gene body (Fuchs et al, 2014a; Jonkers et al, 2014; Veloso et al, 2014).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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“Indeed, fast transcription correlates with distal localization of H3K36me3 (Jonkers et al, 2014).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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“Indeed, genes with the highest measured RNA Pol II velocity have been shown to generate more mRNAs (Danko et al, 2013; Jonkers et al, 2014; Cohen et al, 2018).”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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“Indeed, a positive correlation has been identified between intron 1 size and RNA Pol II speed (Jonkers et al, 2014)”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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“Conversely, exon density correlates negatively with RNA Pol II velocity (Jonkers et al, 2014; Veloso et al, 2014)”
From RNA polymerase II speed: a key player in controlling and adapting transcriptome composition (2021) · cites this paper as Jonkers et al, 2014
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Metadata
- Authors
- Jonkers, I., Kwak, H., & Lis, J. T.
- Affiliations
- Cornell University (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Jonkers, Iris
- Lis, John T
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2014-04-29
- Volume
- 3
- Pages
- e02407-e02407
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC4001325
- OpenAlex
- W2038894647
- Cited by
- 581
- References
- 67
- Citations by year
- 2026: 26 · 2025: 40 · 2024: 52 · 2023: 48 · 2022: 46 · 2021: 74 · 2020: 40 · 2019: 57 · 2018: 53 · 2017: 53 · 2016: 49 · 2015: 35 · 2014: 8
- FWCI
- 19.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (GM25232)
- Helen Hay Whitney Foundation
- Howard Hughes Medical Institute
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- RNA polymerase II elongation, promoter-proximal pausing, transcription kinetics, mouse embryonic stem cells, triptolide, flavopiridol, GRO-seq, H3K79me2, chromatin
- MeSH terms
- Animals, Cells, Cultured, Chromatin, Diterpenes, Epoxy Compounds, Exons, Flavonoids, Humans, Phenanthrenes, Piperidines, Promoter Regions, Genetic, RNA Polymerase II, RNA, Messenger, Transcription, Genetic, Genetic Variation, Gene Library, Sequence Alignment, Sequence Analysis, DNA, Chromatin Immunoprecipitation, Mice, Embryonic Stem Cells, Genetic Association Studies
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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