Evidence map›Paper›PMID 22022255›Full record

ArticlePLoS computational biology2011

Modelling reveals kinetic advantages of co-transcriptional splicing.

Stuart Aitken, Ross D Alexander, Jean D Beggs

Abstract read
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
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

21 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Landscape Zooming toward the Prediction of RNA Cotranscriptional Folding.Journal of chemical theory and computation · 2022
    Article
  5. Article
  6. Article
  7. Article
  8. Perfect timing: splicing and transcription rates in living cells.Wiley interdisciplinary reviews. RNA · 2017
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Complexity of RNA polymerase II elongation dynamics.Biochimica et biophysica acta · 2012
    Review
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.

Stuart AitkenCentre for Systems Biology, University of Edinburgh, Edinburgh, United Kingdom. s.aitken@ed.ac.uk
Ross D Alexander
Jean D Beggs

Funding

Biotechnology and Biological Sciences Research Council BB/D019621Biotechnology and Biological Sciences Research Council BB/D019621/1Wellcome Trust
6 · The paper itself

Abstract

Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Indexed as

Models, GeneticRNA SplicingTranscription, GeneticGenes, FungalGenes, ReporterIntronsKineticsSaccharomyces cerevisiae

Identifiers

PMID22022255
PMCPMC3192812

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.