Evidence map›Paper›PMID 31447549›Full record

ArticleBioinformatics and biology insights2019

Enjoy the Silence: Nearly Half of Human tRNA Genes Are Silent.

Adrian Gabriel Torres

Open access · goldAbstract readComment
In one paragraph

Article in Bioinformatics and biology insights, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
1.7field-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

24 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Review
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  6. Emerging roles of transfer RNA fragments in the CNS.Brain : a journal of neurology · 2025
    Review
  7. Article
  8. Article
  9. Article
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  11. Article
  12. Article
  13. Review
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  15. Article
  16. tRNA Function and Dysregulation in Cancer.Frontiers in cell and developmental biology · 2022
    Review
  17. Review
  18. Article
  19. Article
  20. Transfer RNA and Origins of RNA Interference.Frontiers in molecular biosciences · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Adrian Gabriel TorresInstitute for Research in Biomedicine, Barcelona Institute of Science and Technology, Barcelona, Spain.ORCID https://orcid.org/0000-0002-5479-1325
Institute for Research in Biomedicine · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transfer RNAs (tRNAs) are key components of the translation machinery. They read codons on messenger RNAs (mRNAs) and deliver the appropriate amino acid to the ribosome for protein synthesis. The human genome encodes more than 500 tRNA genes but their individual contribution to the cellular tRNA pool is unclear. In recent years, novel methods were developed to improve the quantification of tRNA gene expression, most of which rely on next-generation sequencing such as small RNA-Seq applied to tRNAs (tRNA-Seq). In a previous study, we presented a bioinformatics strategy to analyse tRNA-Seq datasets that we named 'isodecoder-specific tRNA gene contribution profiling' (Iso-tRNA-CP). Using Iso-tRNA-CP, we showed that tRNA gene expression is cell type- and tissue-specific and that this process can regulate tRNA-derived fragments abundance. An additional observation that stems from that work is that approximately half of human tRNA genes appeared silent or poorly expressed. In this commentary, I discuss this finding in light of the current literature and speculate on potential functions that transcriptionally silent tRNA genes may play. Studying silent tRNA genes may offer a unique opportunity to unravel novel mechanisms of cell regulation associated to tRNA biology.

Indexed as

gene expressionTransfer RNAtRNA-derived fragmentstRNA functiontRNA-Seq

Identifiers

PMID31447549
PMCPMC6688141
OpenAlexW2967315044

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.