Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data

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• dc.contributor.author Ramazzotti, Daniele
• dc.contributor.author Maspero, Davide
• dc.contributor.author Angaroni, Fabrizio
• dc.contributor.author Spinelli, Silvia
• dc.contributor.author Antoniotti, Marco
• dc.contributor.author Piazza, Rocco
• dc.contributor.author Graudenzi, Alex
• dc.date.accessioned 2022-11-02T07:28:51Z
• dc.date.available 2022-11-02T07:28:51Z
• dc.date.issued 2022
• dc.description.abstract A key task of genomic surveillance of infectious viral diseases lies in the early detection of dangerous variants. Unexpected help to this end is provided by the analysis of deep sequencing data of viral samples, which are typically discarded after creating consensus sequences. Such analysis allows one to detect intra-host low-frequency mutations, which are a footprint of mutational processes underlying the origination of new variants. Their timely identification may improve public-health decision-making with respect to traditional approaches exploiting consensus sequences. We present the analysis of 220,788 high-quality deep sequencing SARS-CoV-2 samples, showing that many spike and nucleocapsid mutations of interest associated to the most circulating variants, including Beta, Delta, and Omicron, might have been intercepted several months in advance. Furthermore, we show that a refined genomic surveillance system leveraging deep sequencing data might allow one to pinpoint emerging mutation patterns, providing an automated data-driven support to virologists and epidemiologists.
• dc.format.mimetype application/pdf
• dc.identifier.citation Ramazzotti D, Maspero D, Angaroni F, Spinelli S, Antoniotti M, Piazza R, Graudenzi A. Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data. iScience. 2022 Jun 17;25(6):104487. DOI: 10.1016/j.isci.2022.104487
• dc.identifier.doi http://dx.doi.org/10.1016/j.isci.2022.104487
• dc.identifier.issn 2589-0042
• dc.identifier.uri http://hdl.handle.net/10230/54647
• dc.language.iso eng
• dc.publisher Elsevier
• dc.relation.ispartof iScience. 2022 Jun 17;25(6):104487
• dc.rights © 2022 The Author(s). This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword Bioinformatics
• dc.subject.keyword Genomic analysis
• dc.subject.keyword Microbiology
• dc.subject.keyword Virology
• dc.title Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion