Evidence map›Paper›PMID 27873472›Full record

ReviewWiley interdisciplinary reviews. RNA2017

Perfect timing: splicing and transcription rates in living cells.

Tara Alpert, Lydia Herzel, Karla M Neugebauer

Abstract readReview
In one paragraph

Review in Wiley interdisciplinary reviews. RNA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

60 citing papers in PubMed, 1 synthesis or guideline pooled it, 104 citations in OpenAlex.

  1. Pooled it
  2. Predicting human mRNA isoform levels from site-specific splicing kineticsbioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Long-read Sequencing of Nascent RNA from Budding and Fission Yeasts.bioRxiv : the preprint server for biology · 2025
    Article
  5. Design of a GFP reporter for splicing analysis in mammalian cells.Biotechnology reports (Amsterdam, Netherlands) · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Co-transcriptional gene regulation in eukaryotes and prokaryotes.Nature reviews. Molecular cell biology · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. scCensus: Off-target scRNA-seq reads reveal meaningful biology.bioRxiv : the preprint server for biology · 2024
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Tara AlpertDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Lydia HerzelDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Karla M NeugebauerDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.
Yale University · US

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Skill Development for Diverse Scientific Careers: A New Course Predoctoral Program in Cellular and Molecular BiologyT32GM007223 · NIGMS · YALE UNIVERSITY · PI BASERGA, SUSAN J · 1985 to 2019
$31.0M
Cross-regulation between transcription and pre-mRNA splicingR01GM112766 · NIGMS · YALE UNIVERSITY · PI Karla M Neugebauer · 2015 to 2026
$5.3M
NCATS NIH HHS UL1 TR001863NIGMS NIH HHS R01 GM112766NIGMS NIH HHS T32 GM007223
6 · The paper itself

Abstract

An important step toward understanding gene regulation is the elucidation of the time necessary for the completion of individual steps. Measurement of reaction rates can reveal potential nodes for regulation. For example, measurements of in vivo transcription elongation rates reveal regulation by DNA sequence, gene architecture, and chromatin. Pre-mRNA splicing is regulated by transcription elongation rates and vice versa, yet the rates of RNA processing reactions remain largely elusive. Since the 1980s, numerous model systems and approaches have been used to determine the precise timing of splicing in vivo. Because splicing can be co-transcriptional, the position of Pol II when splicing is detected has been used as a proxy for time by some investigators. In addition to these 'distance-based' measurements, 'time-based' measurements have been possible through live cell imaging, metabolic labeling of RNA, and gene induction. Yet splicing rates can be convolved by the time it takes for transcription, spliceosome assembly and spliceosome disassembly. The variety of assays and systems used has, perhaps not surprisingly, led to reports of widely differing splicing rates in vivo. Recently, single molecule RNA-seq has indicated that splicing occurs more quickly than previously deduced. Here we comprehensively review these findings and discuss evidence that splicing and transcription rates are closely coordinated, facilitating the efficiency of gene expression. On the other hand, introduction of splicing delays through as yet unknown mechanisms provide opportunity for regulation. More work is needed to understand how cells optimize the rates of gene expression for a range of biological conditions. WIREs RNA 2017, 8:e1401. doi: 10.1002/wrna.1401 For further resources related to this article, please visit the WIREs website.

Indexed as

Transcription, GeneticAnimalsCell SurvivalChromatinHumansRNA Polymerase IIRNA SplicingSpliceosomesTime FactorsChromatinRNA Polymerase II

Identifiers

PMID27873472
PMCPMC5355006
OpenAlexW2556628421

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.