Evidence map›Paper›PMID 32066737›Full record

ArticleNature communications2020

A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry.

Samuel Wein, Byron Andrews, Timo Sachsenberg, Helena Santos-Rosa, Oliver Kohlbacher, Tony Kouzarides, Benjamin A Garcia, Hendrik Weisser

Open access · goldAbstract readValidation Study
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

52 citing papers in PubMed, 93 citations in OpenAlex.

  1. Review
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  6. Integrating mass spectrometry with Nanopore direct RNA sequencing forbioRxiv : the preprint server for biology · 2026
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  7. Pseudouridylation landscape across 42bioRxiv : the preprint server for biology · 2026
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  8. Article
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  11. Methods for Investigating the Sperm Epigenome.Advances in experimental medicine and biology · 2026
    Review
  12. The Secret Life of NJournal of molecular biology · 2025
    Review
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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

8 authors at 6 institutions in 3 countries.

Samuel Wein *Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Byron Andrews *STORM Therapeutics Limited, Moneta Building, Babraham Research Campus, Cambridge, UK.
Timo SachsenbergApplied Bioinformatics, Department for Computer Science, University of Tübingen, Tübingen, Germany.
Helena Santos-RosaGurdon Institute, University of Cambridge, Cambridge, UK.
Oliver KohlbacherCenter for Bioinformatics Tübingen, University of Tübingen, Tübingen, Germany.ORCID http://orcid.org/0000-0003-1739-4598
Tony KouzaridesGurdon Institute, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-8918-4162
Benjamin A GarciaEpigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. bgarci@pennmedicine.upenn.edu.
Hendrik WeisserSTORM Therapeutics Limited, Moneta Building, Babraham Research Campus, Cambridge, UK. hendrik.weisser@stormtherapeutics.com.ORCID http://orcid.org/0000-0001-9723-7503
University of Cambridge · GBBernstein Center for Computational Neuroscience Tübingen · DEMax Planck Institute for Developmental Biology · DEMission Therapeutics (United Kingdom) · GBUniversity of Pennsylvania · USUniversity of Tübingen · DE

Funding

Translational Research Support CoreP30ES013508 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI Rebecca A Simmons · 2006 to 2026
$35.3M
Cancer Research UK 27321NIEHS NIH HHS P30 ES013508
6 · The paper itself

Abstract

The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.

Indexed as

Search EngineBase SequenceDatabases, FactualDatasets as TopicEpigenomicsHigh-Throughput Screening AssaysHumansOligonucleotidesReproducibility of ResultsRNA Processing, Post-TranscriptionalRNA, TransferTandem Mass SpectrometryOligonucleotidesRNA, Transfer

Identifiers

PMID32066737
PMCPMC7026122
OpenAlexW3005935287

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.