Evidence map›Paper›PMID 23818636›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Characterization and comparison of human nuclear and cytosolic editomes.

Liang Chen

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. WidespreadRNA (New York, N.Y.) · 2019
    Article
  19. Review
  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

1 author.

Liang ChenDepartment of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA. liang.chen@usc.edu

Funding

Implications of haplotype structure in the human genomeP50HG002790 · NHGRI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI TAVARE, SIMON · 2003 to 2013
$29.9M
Statistical methods for the study of alternative splicing using deep sequencingR01GM097230 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI CHEN, LIANG · 2011 to 2014
$1.4M
NHGRI NIH HHS P50 HG002790NHGRI NIH HHS P50HG002790NIGMS NIH HHS R01 GM097230NIGMS NIH HHS R01GM097230
6 · The paper itself

Abstract

We developed a robust computational statistical framework to identify RNA editing events from RNA-Seq data with high specificity. Our approach handles several outstanding challenges of genome-wide editing analyses, including the effect of editing on read alignment and the utilization of redundant reads. By applying this framework, we characterized the nuclear and cytosolic editomes of seven human cell lines. We found that 93.8-99.2% of the editing events are A-to-G (or A-to-I). Nuclear transcriptomes contain many more editing events than cytosolic transcriptomes. Most of the sites exhibiting nucleus-specific editing are in introns or novel intergenic transcripts that are preferentially localized in the nucleus regardless of their editing status, arguing against the role of editing in nuclear retention. In contrast, many sites that exhibit cytosol-specific editing show comparable nuclear and cytosolic expression, suggesting the differential subcellular compartmentalization of the edited and the unedited alleles. We found that RNA editing is globally associated with the modification of microRNA regulation in 3' untranslated regions, whereas editing events in coding regions are rare and tend to be synonymous. Interestingly, A-to-G editing at derived alleles in the human lineage tends to result in reversion back to the ancestral forms at the RNA level. This suggests that editing can mediate RNA memory on evolutionary time-scales to maintain ancestral genetic information.

Indexed as

AlgorithmsEvolution, MolecularModels, GeneticBase SequenceCell LineComputational BiologyHigh-Throughput Nucleotide SequencingHumansMicroRNAsMolecular Sequence DataRNA EditingMicroRNAshigh-throughput sequencingnucleo-cytoplasmic localization

Identifiers

PMID23818636
PMCPMC3718162

What OpenQuestion holds

Textmetadata
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.