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

Base Sequence / genetics Databases, Factual / statistics & numerical data Datasets as Topic Epigenomics / methods High-Throughput Screening Assays / methods Humans Oligonucleotides / chemistry RNA Processing, Post-Transcriptional / genetics RNA, Transfer / chemistry Reproducibility of Results Search Engine Tandem Mass Spectrometry / methods

Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
17 02 2020
Historique:
received: 11 02 2019
accepted: 22 01 2020
entrez: 19 2 2020
pubmed: 19 2 2020
medline: 6 5 2020
Statut: epublish

Résumé

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.

Identifiants

DOI: 10.1038/s41467-020-14665-7 PMID: 32066737 PMC: PMC7026122
pubmed: 32066737
doi: 10.1038/s41467-020-14665-7
pii: 10.1038/s41467-020-14665-7
pmc: PMC7026122
doi:

Substances chimiques

Oligonucleotides 0
RNA, Transfer 9014-25-9

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

926

Subventions

Organisme : NIEHS NIH HHS
ID : P30 ES013508
Pays : United States

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Auteurs

Samuel Wein (S)

Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Center for Bioinformatics Tübingen, University of Tübingen, Tübingen, Germany.

Byron Andrews (B)

STORM Therapeutics Limited, Moneta Building, Babraham Research Campus, Cambridge, UK.

Timo Sachsenberg (T)

Applied Bioinformatics, Department for Computer Science, University of Tübingen, Tübingen, Germany.

Helena Santos-Rosa (H)

Gurdon Institute, University of Cambridge, Cambridge, UK.

Oliver Kohlbacher (O)

Center for Bioinformatics Tübingen, University of Tübingen, Tübingen, Germany.
Applied Bioinformatics, Department for Computer Science, University of Tübingen, Tübingen, Germany.
Quantitative Biology Center, University of Tübingen, Tübingen, Germany.
Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany.
Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.
ORCID: 0000-0003-1739-4598

Tony Kouzarides (T)

Gurdon Institute, University of Cambridge, Cambridge, UK.
ORCID: 0000-0002-8918-4162

Benjamin A Garcia (BA)

Epigenetics Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. bgarci@pennmedicine.upenn.edu.

Hendrik Weisser (H)

STORM Therapeutics Limited, Moneta Building, Babraham Research Campus, Cambridge, UK. hendrik.weisser@stormtherapeutics.com.
ORCID: 0000-0001-9723-7503

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Classifications MeSH

questionsmedicales.fr › Sciences de l'information › Sources d'information › Services d'information › Documentation › Données de séquences moléculaires › Séquence nucléotidique › A computational platform for high-throughput...
questionsmedicales.fr › Sciences de l'information › Mémorisation et recherche des informations › Bases de données comme sujet › Bases de données factuelles › A computational platform for high-throughput...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Collecte de données › Jeux de données comme sujet › A computational platform for high-throughput...
questionsmedicales.fr › Disciplines des sciences naturelles › Disciplines des sciences biologiques › Biologie › Génétique › Génomique › Épigénomique › A computational platform for high-throughput...
questionsmedicales.fr › Techniques d'investigation › Tests de criblage à haut débit › A computational platform for high-throughput...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › A computational platform for high-throughput...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Nucléotides › Polynucléotides › Oligonucléotides › A computational platform for high-throughput...
questionsmedicales.fr › Phénomènes génétiques › Régulation de l'expression des gènes › Maturation post-transcriptionnelle des ARN › A computational platform for high-throughput...
questionsmedicales.fr › Acides nucléiques, nucléotides et nucléosides › Acides nucléiques › ARN › ARN de transfert › A computational platform for high-throughput...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Méthodologie en recherche épidémiologique › Reproductibilité des résultats › A computational platform for high-throughput...
questionsmedicales.fr › Sciences de l'information › Mémorisation et recherche des informations › Moteur de recherche › A computational platform for high-throughput...
questionsmedicales.fr › Techniques d'investigation › Techniques de chimie analytique › Spectrométrie de masse › Spectrométrie de masse en tandem › A computational platform for high-throughput...