EpiNano: detection of m6A RNA modifications using Oxford nanopore direct RNA sequencing

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• dc.contributor.author Liu, Huanle
• dc.contributor.author Begik, Oguzhan
• dc.contributor.author Novoa, Eva Maria
• dc.date.accessioned 2021-07-23T06:58:44Z
• dc.date.issued 2021
• dc.description.abstract RNA modifications play pivotal roles in the RNA life cycle and RNA fate, and are now appreciated as a major posttranscriptional regulatory layer in the cell. In the last few years, direct RNA nanopore sequencing (dRNA-seq) has emerged as a promising technology that can provide single-molecule resolution maps of RNA modifications in their native RNA context. While native RNA can be successfully sequenced using this technology, the detection of RNA modifications is still challenging. Here, we provide an upgraded version of EpiNano (version 1.2), an algorithm to predict m6A RNA modifications from dRNA-seq datasets. The latest version of EpiNano contains models for predicting m6A RNA modifications in dRNA-seq data that has been base-called with Guppy. Moreover, it can now train models with features extracted from both base-called dRNA-seq FASTQ data and raw FAST5 nanopore outputs. Finally, we describe how EpiNano can be used in stand-alone mode to extract base-calling "error" features and current intensity information from dRNA-seq datasets. In this chapter, we provide step-by-step instructions on how to produce in vitro transcribed constructs to train EpiNano, as well as detailed information on how to use EpiNano to train, test, and predict m6A RNA modifications in dRNA-seq data.
• dc.description.sponsorship We thank all members of the Novoa lab for their valuable insights and discussion. We thank Rebeca Medina for obtaining the TapeStation image used for Fig. 1. OB is supported by an international PhD fellowship (UIPA) from the University of New South Wales. This work was supported by the Australian Research Council (DP180103571 to EMN) and the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) (PGC2018-098152-A-100 to EMN). We acknowledge the support of the MEIC to the EMBL partnership, Centro de Excelencia Severo Ochoa, and CERCA Program/Generalitat de Catalunya.
• dc.format.mimetype application/pdf
• dc.identifier.citation Liu H, Begik O, Novoa EM. EpiNano: detection of m6A RNA modifications using Oxford nanopore direct RNA sequencing. Methods Mol Biol. 2021;2298:31-52. DOI: 10.1007/978-1-0716-1374-0_3
• dc.identifier.doi http://dx.doi.org/10.1007/978-1-0716-1374-0_3
• dc.identifier.issn 1064-3745
• dc.identifier.uri http://hdl.handle.net/10230/48286
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof Methods Mol Biol. 2021;2298:31-52
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/PGC2018-098152-A-100
• dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-1-0716-1374-0_3.
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Base-calling “errors”
• dc.subject.keyword Direct RNA sequencing
• dc.subject.keyword In vitro transcription
• dc.subject.keyword N6-methyladenosine
• dc.subject.keyword Nanopore sequencing
• dc.subject.keyword Native RNA
• dc.subject.keyword Oxford Nanopore Technologies
• dc.subject.keyword RNA modification
• dc.subject.keyword Support vector machine
• dc.title EpiNano: detection of m6A RNA modifications using Oxford nanopore direct RNA sequencing
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/acceptedVersion