Evidence map›Paper›PMID 24699680›Full record

ArticlePloS one2014

Characterization of human pseudogene-derived non-coding RNAs for functional potential.

Xingyi Guo, Mingyan Lin, Shira Rockowitz, Herbert M Lachman, Deyou Zheng

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 15% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. International journal of molecular sciences · 2021
    Article
  11. Article
  12. Pseudogenes: Four Decades of Discovery.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Identification of Potential Diagnostic and Prognostic Pseudogenes in Hepatocellular Carcinoma Based on Pseudogene-miRNA-mRNA Competitive Network.Medical science monitor : international medical journal of experimental and clinical research · 2020
    Article
  18. Review
  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

5 authors at 1 institution in 1 country.

Xingyi GuoThe Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America.
Mingyan LinDepartment of Genetics, Albert Einstein College of Medicine, New York, New York, United States of America.
Shira RockowitzDepartment of Genetics, Albert Einstein College of Medicine, New York, New York, United States of America.
Herbert M LachmanDepartment of Genetics, Albert Einstein College of Medicine, New York, New York, United States of America; Department of Neuroscience, Albert Einstein College of Medicine, New York, New York, United States of America; Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, New York, New York, United States of America.
Deyou ZhengThe Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, New York, New York, United States of America; Department of Genetics, Albert Einstein College of Medicine, New York, New York, United States of America; Department of Neuroscience, Albert Einstein College of Medicine, New York, New York, United States of America.
Albert Einstein College of Medicine · US

Funding

Novel regulatory network involving non-coding role of an ASD candidate gene PTENR21MH099452 · NIMH · ALBERT EINSTEIN COLLEGE OF MEDICINE · PI ZHENG, DEYOU · 2012 to 2013
$449k
NIMH NIH HHS R21 MH099452NIMH NIH HHS R21MH099452
6 · The paper itself

Abstract

Thousands of pseudogenes exist in the human genome and many are transcribed, but their functional potential remains elusive and understudied. To explore these issues systematically, we first developed a computational pipeline to identify transcribed pseudogenes from RNA-Seq data. Applying the pipeline to datasets from 16 distinct normal human tissues identified ∼ 3,000 pseudogenes that could produce non-coding RNAs in a manner of low abundance but high tissue specificity under normal physiological conditions. Cross-tissue comparison revealed that the transcriptional profiles of pseudogenes and their parent genes showed mostly positive correlations, suggesting that pseudogene transcription could have a positive effect on the expression of their parent genes, perhaps by functioning as competing endogenous RNAs (ceRNAs), as previously suggested and demonstrated with the PTEN pseudogene, PTENP1. Our analysis of the ENCODE project data also found many transcriptionally active pseudogenes in the GM12878 and K562 cell lines; moreover, it showed that many human pseudogenes produced small RNAs (sRNAs) and some pseudogene-derived sRNAs, especially those from antisense strands, exhibited evidence of interfering with gene expression. Further integrated analysis of transcriptomics and epigenomics data, however, demonstrated that trimethylation of histone 3 at lysine 9 (H3K9me3), a posttranslational modification typically associated with gene repression and heterochromatin, was enriched at many transcribed pseudogenes in a transcription-level dependent manner in the two cell lines. The H3K9me3 enrichment was more prominent in pseudogenes that produced sRNAs at pseudogene loci and their adjacent regions, an observation further supported by the co-enrichment of SETDB1 (a H3K9 methyltransferase), suggesting that pseudogene sRNAs may have a role in regional chromatin repression. Taken together, our comprehensive and systematic characterization of pseudogene transcription uncovers a complex picture of how pseudogene ncRNAs could influence gene and pseudogene expression, at both epigenetic and post-transcriptional levels.

Indexed as

Genome, HumanPseudogenesRNA, UntranslatedHumansTranscription, GeneticRNA, Untranslated

Identifiers

PMID24699680
PMCPMC3974860
OpenAlexW2022745948

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.