RNAProbe: a web server for normalization and analysis of RNA structure probing data.


Journal

Nucleic acids research
ISSN: 1362-4962
Titre abrégé: Nucleic Acids Res
Pays: England
ID NLM: 0411011

Informations de publication

Date de publication:
02 07 2020
Historique:
accepted: 05 06 2020
revised: 02 05 2020
received: 07 03 2020
pubmed: 7 6 2020
medline: 8 10 2020
entrez: 7 6 2020
Statut: ppublish

Résumé

RNA molecules play key roles in all living cells. Knowledge of the structural characteristics of RNA molecules allows for a better understanding of the mechanisms of their action. RNA chemical probing allows us to study the susceptibility of nucleotides to chemical modification, and the information obtained can be used to guide secondary structure prediction. These experimental results can be analyzed using various computational tools, which, however, requires additional, tedious steps (e.g., further normalization of the reactivities and visualization of the results), for which there are no fully automated methods. Here, we introduce RNAProbe, a web server that facilitates normalization, analysis, and visualization of the low-pass SHAPE, DMS and CMCT probing results with the modification sites detected by capillary electrophoresis. RNAProbe automatically analyzes chemical probing output data and turns tedious manual work into a one-minute assignment. RNAProbe performs normalization based on a well-established protocol, utilizes recognized secondary structure prediction methods, and generates high-quality images with structure representations and reactivity heatmaps. It summarizes the results in the form of a spreadsheet, which can be used for comparative analyses between experiments. Results of predictions with normalized reactivities are also collected in text files, providing interoperability with bioinformatics workflows. RNAProbe is available at https://rnaprobe.genesilico.pl.

Identifiants

pubmed: 32504492
pii: 5854141
doi: 10.1093/nar/gkaa396
pmc: PMC7319577
doi:

Substances chimiques

Riboswitch 0
RNA 63231-63-0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

W292-W299

Informations de copyright

© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.

Références

RNA. 1995 Jun;1(4):351-62
pubmed: 7493314
Bioinformatics. 2017 Jan 15;33(2):306-308
pubmed: 27663500
Cell. 2009 Feb 20;136(4):577-80
pubmed: 19239877
Nat Protoc. 2006;1(3):1610-6
pubmed: 17406453
Brief Bioinform. 2020 May 08;:
pubmed: 32382747
BMC Bioinformatics. 2016 May 17;17(1):215
pubmed: 27188311
Methods. 2010 Oct;52(2):150-8
pubmed: 20554050
Nucleic Acids Res. 2015 Sep 30;43(17):8540-50
pubmed: 26250109
Nucleic Acids Res. 2016 Jul 8;44(W1):W294-301
pubmed: 27137891
Biochemistry. 2012 Sep 11;51(36):7037-9
pubmed: 22913637
Nature. 2017 Jan 12;541(7636):242-246
pubmed: 27841871
RNA. 2013 Jan;19(1):63-73
pubmed: 23188808
BMC Bioinformatics. 2010 Mar 15;11:129
pubmed: 20230624
Algorithms Mol Biol. 2011 Nov 24;6:26
pubmed: 22115189
Cell Mol Gastroenterol Hepatol. 2016 Jan 09;2(3):281-301.e9
pubmed: 28174720
RNA. 2017 Feb;23(2):169-174
pubmed: 27879433
Methods Mol Biol. 2014;1086:79-94
pubmed: 24136599
Cell. 2002 Nov 27;111(5):747-56
pubmed: 12464185
Chem Biol. 2004 Dec;11(12):1729-41
pubmed: 15610857
Nucleic Acids Res. 2009 Jul;37(Web Server issue):W277-80
pubmed: 19435882
Nucleic Acids Res. 2018 Sep 19;46(16):e97
pubmed: 29893890
Proc Natl Acad Sci U S A. 2013 Apr 2;110(14):5498-503
pubmed: 23503844
Bioinformatics. 2011 Jul 1;27(13):i85-93
pubmed: 21685106
J Biol Chem. 1988 Oct 15;263(29):15166-75
pubmed: 3049601
Methods Enzymol. 1988;164:481-9
pubmed: 2468070
Biochemistry. 2013 Dec 3;52(48):8777-85
pubmed: 24215455
Proc Natl Acad Sci U S A. 2009 Jan 6;106(1):97-102
pubmed: 19109441
Elife. 2018 Feb 15;7:
pubmed: 29446752
Bioinformatics. 2009 Aug 1;25(15):1974-5
pubmed: 19398448
Proc Natl Acad Sci U S A. 1980 Aug;77(8):4679-82
pubmed: 6159633
Bioinformatics. 2006 Jul 15;22(14):e90-8
pubmed: 16873527
Nucleic Acids Res. 2016 Jul 8;44(W1):W315-9
pubmed: 27095203
Mol Microbiol. 1998 Nov;30(4):737-49
pubmed: 10094622
J Am Chem Soc. 2005 Mar 30;127(12):4223-31
pubmed: 15783204
Bioinformatics. 2015 Aug 15;31(16):2668-75
pubmed: 25886980
Proc Natl Acad Sci U S A. 2014 Sep 23;111(38):13858-63
pubmed: 25205807
Bioinformatics. 2019 Jul 15;35(14):i295-i304
pubmed: 31510672
Cell. 1981 Dec;27(3 Pt 2):487-96
pubmed: 6101203
Nature. 2013 Jul 18;499(7458):355-9
pubmed: 23842498

Auteurs

Tomasz K Wirecki (TK)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.

Katarzyna Merdas (K)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.

Agata Bernat (A)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.

Michał J Boniecki (MJ)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.

Janusz M Bujnicki (JM)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.
Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, ul. Umultowska 89, PL-61-614 Poznan, Poland.

Filip Stefaniak (F)

Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology in Warsaw, ul. Ks. Trojdena 4, PL-02-109 Warsaw, Poland.

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