Evidence map›Paper›PMID 27613580›Full record

ArticleRNA (New York, N.Y.)2016

tRNA base methylation identification and quantification via high-throughput sequencing.

Wesley C Clark, Molly E Evans, Dan Dominissini, Guanqun Zheng, Tao Pan

Abstract read
In one paragraph

Article in RNA (New York, N.Y.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers.

0numbers the graph read from it
0cells of the map it votes in
146citing 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

146 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Optimized tRNA structure-seq reveals robust tRNA secondary structures inbioRxiv : the preprint server for biology · 2026
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. The Secret Life of NJournal of molecular biology · 2025
    Review
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article

86 more citing papers are in PubMed but not listed here.

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.

Wesley C ClarkDepartment of Biochemistry and Molecular Biology.
Molly E EvansDepartment of Biochemistry and Molecular Biology.
Dan DominissiniDepartment of Chemistry, University of Chicago, Chicago, Illinois 60637, USA.
Guanqun ZhengDepartment of Biochemistry and Molecular Biology.
Tao PanDepartment of Biochemistry and Molecular Biology.

Funding

Predoctoral Training Program in Chemistry & BiologyT32GM008720 · NIGMS · UNIVERSITY OF CHICAGO · PI PICCIRILLI, JOSEPH ANTHONY · 1999 to 2020
$4.7M
Mis-translation as a new mechanism of stress response in biologyDP1GM105386 · NIGMS · UNIVERSITY OF CHICAGO · PI PAN, TAO · 2012 to 2015
$3.1M
NIGMS NIH HHS DP1 GM105386NIGMS NIH HHS T32 GM008720
6 · The paper itself

Abstract

Eukaryotic transfer RNAs contain on average 14 modifications. Investigations of their biological functions require the determination of the modification sites and the dynamic variations of the modification fraction. Base methylation represents a major class of tRNA modification. Although many approaches have been used to identify tRNA base methylations, including sequencing, they are generally qualitative and do not report the information on the modification fraction. Dynamic mRNA modifications have been shown to play important biological roles; yet, the extent of tRNA modification fractions has not been reported systemically. Here we take advantage of a recently developed high-throughput sequencing method (DM-tRNA-seq) to identify and quantify tRNA base methylations located at the Watson-Crick face in HEK293T cells at single base resolution. We apply information derived from both base mutations and positional stops from sequencing using a combination of demethylase treatment and cDNA synthesis by a thermophilic reverse transcriptase to compile a quantitative "Modification Index" (MI) for six base methylations in human tRNA and rRNA. MI combines the metrics for mutational and stop components from alignment of sequencing data without demethylase treatment, and the modifications are validated in the sequencing data upon demethylase treatment. We identify many new methylation sites in both human nuclear and mitochondrial-encoded tRNAs not present in the RNA modification databases. The potentially quantitative nature of the MI values obtained from sequencing is validated by primer extension of several tRNAs. Our approach should be widely applicable to identify tRNA methylation sites, analyze comparative fractional modifications, and evaluate the modification dynamics between different samples.

Indexed as

HEK293 CellsHigh-Throughput Nucleotide SequencingHumansMethylationRNA, TransferRNA, Transferhigh-throughput sequencingmethylationmodificationquantificationtRNA

Identifiers

PMID27613580
PMCPMC5066629

What OpenQuestion holds

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LicenceCC BY-NC
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.