Evidence map›Paper›PMID 37802215›Full record

ArticleJournal of molecular biology2023

MRT-ModSeq - Rapid Detection of RNA Modifications with MarathonRT.

Rafael de Cesaris Araujo Tavares, Gandhar Mahadeshwar, Han Wan, Anna Marie Pyle

Abstract read
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In one paragraph

Article in Journal of molecular biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. A B1 SINE element within the mouseScience advances · 2026
    Article
  3. Identifying RNA acInterdisciplinary sciences, computational life sciences · 2026
    Article
  4. Article
  5. Article
  6. SnoRNA Expression and RNA 2'-O-Methylation inbioRxiv : the preprint server for biology · 2026
    Article
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Rafael de Cesaris Araujo TavaresDepartment of Chemistry, Yale University, New Haven, CT 06511, USA.
Gandhar MahadeshwarDepartment of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06511, USA. Electronic address: https://twitter.com/gandzmakerdance.
Han WanDepartment of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA. Electronic address: https://twitter.com/HanWan19744358.
Anna Marie PyleDepartment of Chemistry, Yale University, New Haven, CT 06511, USA; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA. Electronic address: anna.pyle@yale.edu.

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Chemical modifications are essential regulatory elements that modulate the behavior and function of cellular RNAs. Despite recent advances in sequencing-based RNA modification mapping, methods combining accuracy and speed are still lacking. Here, we introduce MRT-ModSeq for rapid, simultaneous detection of multiple RNA modifications using MarathonRT. MRT-ModSeq employs distinct divalent cofactors to generate 2-D mutational profiles that are highly dependent on nucleotide identity and modification type. As a proof of concept, we use the MRT fingerprints of well-studied rRNAs to implement a general workflow for detecting RNA modifications. MRT-ModSeq rapidly detects positions of diverse modifications across a RNA transcript, enabling assignment of m1acp3Y, m1A, m3U, m7G and 2'-OMe locations through mutation-rate filtering and machine learning. m1A sites in sparsely modified targets, such as MALAT1 and PRUNE1 could also be detected. MRT-ModSeq can be trained on natural and synthetic transcripts to expedite detection of diverse RNA modification subtypes across targets of interest.

Indexed as

RNA Processing, Post-TranscriptionalRNA, RibosomalHumansMutationSequence Analysis, RNARNA, RibosomalEpitranscriptomicsgroup II reverse transcriptasemachine learningmutational profilingRNA processing

Identifiers

What OpenQuestion holds

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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.