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dc.contributor.authorPardo Seco, Jacobo José
dc.contributor.authorBello, X.
dc.contributor.authorGómez Carballa, Alberto
dc.contributor.authorMartinón Torres, Federico 
dc.contributor.authorMuñoz-Barús, J.I.
dc.contributor.authorSalas Ellacuriaga, Antonio
dc.date.accessioned2025-08-26T10:53:06Z
dc.date.available2025-08-26T10:53:06Z
dc.date.issued2022
dc.identifier.citationPardo-Seco J, Bello X, Gómez-Carballa A, Martinón-Torres F, Muñoz-Barús JI, Salas A. A Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations. International Journal of Molecular Sciences. 2022;23(21).
dc.identifier.issn1422-0067
dc.identifier.otherhttps://portalcientifico.sergas.gal/documentos/638be9ea840d3a6d9ac81ebd*
dc.identifier.urihttp://hdl.handle.net/20.500.11940/20721
dc.description.abstractEstablishing the timeframe when a particular virus was circulating in a population could be useful in several areas of biomedical research, including microbiology and legal medicine. Using simulations, we demonstrate that the circulation timeframe of an unknown SARS-CoV-2 genome in a population (hereafter, estimated time of a queried genome [QG]; tE-QG) can be easily predicted using a phylogenetic model based on a robust reference genome database of the virus, and information on their sampling dates. We evaluate several phylogeny-based approaches, including modeling evolutionary (substitution) rates of the SARS-CoV-2 genome (~10?3 substitutions/nucleotide/year) and the mutational (substitutions) differences separating the QGs from the reference genomes (RGs) in the database. Owing to the mutational characteristics of the virus, the present Viral Molecular Clock Dating (VMCD) method covers timeframes going backwards from about a month in the past. The method has very low errors associated to the tE-QG estimates and narrow intervals of tE-QG, both ranging from a few days to a few weeks regardless of the mathematical model used. The SARS-CoV-2 model represents a proof of concept that can be extrapolated to any other microorganism, provided that a robust genome sequence database is available. Besides obvious applications in epidemiology and microbiology investigations, there are several contexts in forensic casework where estimating tE-QG could be useful, including estimation of the postmortem intervals (PMI) and the dating of samples stored in hospital settings.en
dc.description.sponsorshipThis study received support from Instituto de Salud Carlos III (ISCIII): GePEM (PI16/01478/Cofinanciado FEDER; A.S.), DIAVIR (DTS19/00049/Cofinanciado FEDER, A.S.), Resvi-Omics (PI19/01039/Cofinanciado FEDER, A.S.), ReSVinext (PI16/01569/Cofinanciado FEDER, F.M.T.), Enterogen (PI19/01090/Cofinanciado FEDER, F.M.T.); Agencia Gallega para la Gestion del Conocimiento en Salud (ACIS): BI-BACVIR (PRIS-3, A.S.), and CovidPhy (SA 304 C, A.S.); Agencia Gallega de Innovacion (GAIN): Grupos con Potencial de Crecimiento (IN607B 2020/08, A.S.), GEN-COVID (IN845D 2020/23, F.M.T.); Framework Partnership Agreement between the Conselleria de Sanidad de la XUNTA de Galicia and GENVIP-IDIS-2021-2024 (SERGAS-IDIS march 2021); and consorcio Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias (CB21/06/00103; F.M.T.); Grant from Xunta de Galicia-Spain [Proxectos Plan Galego IDT (ED431C 2021/35; I.M.B.).en
dc.language.isoeng
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleA Timeframe for SARS-CoV-2 Genomes: A Proof of Concept for Postmortem Interval Estimations*
dc.typeArticleen
dc.authorsophosPardo-Seco, A. J.
dc.authorsophosBello, X.
dc.authorsophosGómez-Carballa, A.
dc.authorsophosMartinón-Torres, F.
dc.authorsophosMuñoz-Barús, J. I.
dc.authorsophosSalas
dc.identifier.doi10.3390/ijms232112899
dc.identifier.sophos638be9ea840d3a6d9ac81ebd
dc.issue.number21
dc.journal.titleInternational Journal of Molecular Sciences*
dc.relation.projectIDInstituto de Salud Carlos III (ISCIII) [PI16/01478, DTS19/00049, PI19/01039, PI16/01569, PI19/01090]; Agencia Gallega para la Gestion del Conocimiento en Salud (ACIS); Agencia Gallega de Innovacion (GAIN): Grupos con Potencial de Crecimiento [IN607B 2020/08, IN845D 2020/23]; Conselleria de Sanidad de la XUNTA de Galicia; consorcio Centro de Investigacion Biomedica en Red de Enfermedades Respiratorias [CB21/06/00103]; Xunta de Galicia-Spain [ED431C 2021/35]
dc.relation.publisherversionhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9656715/pdf/ijms-23-12899.pdf;https://mdpi-res.com/d_attachment/ijms/ijms-23-12899/article_deploy/ijms-23-12899-v2.pdf?version=1667552467es
dc.rights.accessRightsopenAccess
dc.subject.keywordAS Santiagoes
dc.subject.keywordIDISes
dc.subject.keywordCHUSes
dc.typefidesArtículo Científico (incluye Original, Original breve, Revisión Sistemática y Meta-análisis)es
dc.typesophosArtículo Originales
dc.volume.number23


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