Evidence map›Paper›PMID 37292902›Full record

ArticlebioRxiv : the preprint server for biology2023

MRT-ModSeq - Rapid detection of RNA modifications with MarathonRT.

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

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.
Han WanDepartment of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, 06511, USA.
Anna Marie PyleDepartment of Chemistry, Yale University, New Haven, CT, 06511, USA.

Funding

High-throughput detection of transcriptomic and epitranscriptomic variation and kinetics using MarathonRTR01HG011868 · NHGRI · YALE UNIVERSITY · PI GRAVELEY, BRENTON R., PYLE, ANNA MARIE · 2021 to 2024
$3.9M
NHGRI NIH HHS R01 HG011868
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.

Identifiers

PMID37292902
PMCPMC10245971

What OpenQuestion holds

Textmetadata
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.