Evidence map›Paper›PMID 26148686›Full record

ReviewChromosoma2016

The dynamic epitranscriptome: A to I editing modulates genetic information.

Mansoureh Tajaddod, Michael F Jantsch, Konstantin Licht

Open access · hybridAbstract readReview
In one paragraph

Review in Chromosoma, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

25 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Epitranscriptomics in Normal and Malignant Hematopoiesis.International journal of molecular sciences · 2020
    Review
  13. Review
  14. Sex-Dependent RNA Editing andFrontiers in cell and developmental biology · 2020
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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 at 3 institutions in 1 country.

Mansoureh TajaddodDepartment of Chromosome Biology, Max F. Perutz Laboratories, University of Vienna, Dr. Bohr Gasse 9/5, A-1030, Vienna, Austria.
Michael F JantschDepartment of Chromosome Biology, Max F. Perutz Laboratories, University of Vienna, Dr. Bohr Gasse 9/5, A-1030, Vienna, Austria. Michael.Jantsch@univie.ac.at.
Konstantin LichtDepartment of Chromosome Biology, Max F. Perutz Laboratories, University of Vienna, Dr. Bohr Gasse 9/5, A-1030, Vienna, Austria. konstantin.licht@univie.ac.at.
Max Perutz Labs · ATMedical University of Vienna · ATUniversity of Vienna · AT

Funding

Austrian Science Fund FWF P 26845Austrian Science Fund FWF P 26882
6 · The paper itself

Abstract

Adenosine to inosine editing (A to I editing) is a cotranscriptional process that contributes to transcriptome complexity by deamination of adenosines to inosines. Initially, the impact of A to I editing has been described for coding targets in the nervous system. Here, A to I editing leads to recoding and changes of single amino acids since inosine is normally interpreted as guanosine by cellular machines. However, more recently, new roles for A to I editing have emerged: Editing was shown to influence splicing and is found massively in Alu elements. Moreover, A to I editing is required to modulate innate immunity. We summarize the multiple ways in which A to I editing generates transcriptome variability and highlight recent findings in the field.

Indexed as

InosineRNA EditingAdenosineAnimalsDeaminationHumansImmunity, InnateMammalsRNA, MessengerRNA SplicingTranscriptomeAdenosineInosineRNA, Messenger

Identifiers

PMID26148686
PMCPMC4761006
OpenAlexW768616932

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.