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dc.contributor.authorPalencia Madrid, Leire
dc.contributor.authorXavier, Catarina
dc.contributor.authorDe la Puente, María
dc.contributor.authorHohoff, Carsten
dc.contributor.authorPhillips, Christopher
dc.contributor.authorKayser, Manfred
dc.contributor.authorParson, Walther
dc.date.accessioned2020-07-02T11:23:30Z
dc.date.available2020-07-02T11:23:30Z
dc.date.issued2020-06-26
dc.identifier.citationGenes 11(6) : (2020) // Article ID 708es_ES
dc.identifier.issn2073-4425
dc.identifier.urihttp://hdl.handle.net/10810/44857
dc.description.abstractThe study of DNA to predict externally visible characteristics (EVCs) and the biogeographical ancestry (BGA) from unknown samples is gaining relevance in forensic genetics. Technical developments in Massively Parallel Sequencing (MPS) enable the simultaneous analysis of hundreds of DNA markers, which improves successful Forensic DNA Phenotyping (FDP). The EU-funded VISAGE (VISible Attributes through GEnomics) Consortium has developed various targeted MPS-based lab tools to apply FDP in routine forensic analyses. Here, we present an evaluation of the VISAGE Basic tool for appearance and ancestry prediction based on PowerSeq chemistry (Promega) on a MiSeq FGx System (Illumina). The panel consists of 153 single nucleotide polymorphisms (SNPs) that provide information about EVCs (41 SNPs for eye, hair and skin color from HIrisPlex-S) and continental BGA (115 SNPs; three overlap with the EVCs SNP set). The assay was evaluated for sensitivity, repeatability and genotyping concordance, as well as its performance with casework-type samples. This targeted MPS assay provided complete genotypes at all 153 SNPs down to 125 pg of input DNA and 99.67% correct genotypes at 50 pg. It was robust in terms of repeatability and concordance and provided useful results with casework-type samples. The results suggest that this MPS assay is a useful tool for basic appearance and ancestry prediction in forensic genetics for users interested in applying PowerSeq chemistry and MiSeq for this purpose.es_ES
dc.description.sponsorshipThe study received support from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 740580 within the framework of the VISible Attributes through GEnomics (VISAGE) Project and Consortium. L.P.-M. is a recipient of a postdoctoral fellowship from the Doctoral Research Staff Improvement Program of the Basque Government Department of Education (POS_2018_1_0037). M.d.l.P. is funded from a grant provided by the Consellería de Cultura, Educación e Ordenación Universitaria and the Consellería de Economía, Emprego e Industria of the Xunta de Galicia (ED481B 2017/088). The 1000 Genomes high coverage sequence data were generated at the New York Genome Center with funds provided by NHGRI Grant 3UM1HG008901-03S1.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/740580es_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subjectforensic DNA phenotypinges_ES
dc.subjectappearancees_ES
dc.subjectancestryes_ES
dc.subjectBGAes_ES
dc.subjectHIrisPlex-Ses_ES
dc.subjectEVC predictiones_ES
dc.subjectphenotype predictiones_ES
dc.subjectDNA phenotypinges_ES
dc.subjectPowerSeqes_ES
dc.subjectVISAGEes_ES
dc.titleEvaluation of the VISAGE Basic Tool for Appearance and Ancestry Prediction Using PowerSeq Chemistry on the MiSeq FGx Systemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2020-06-30T16:27:03Z
dc.rights.holder2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2073-4425/11/6/708/htmes_ES
dc.contributor.funderEuropean Commission
dc.departamentoesZoología y biología celular animal
dc.departamentoeuZoologia eta animalia zelulen biologia


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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).