Forensic evaluation of the Asia Pacific ancestry-informative MAPlex assay

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Ciencias Forenses, Anatomía Patolóxica, Xinecoloxía e Obstetricia, e Pediatríagl
dc.contributor.authorXavier, Catarina
dc.contributor.authorPuente Vila, María del Carmen de la
dc.contributor.authorPhillips, Christopher Paul
dc.contributor.authorEduardoff, Mayra
dc.contributor.authorHeidegger, A.
dc.contributor.authorMosquera Miguel, Ana
dc.contributor.authorFreire Aradas, Ana María
dc.contributor.authorLagacé, Robert E.
dc.contributor.authorWootton, Sharon Chao
dc.contributor.authorPower, Daniel
dc.contributor.authorParson, Walther
dc.contributor.authorLareu Huidobro, María Victoria
dc.contributor.authorDaniel, Runa
dc.date.accessioned2021-01-19T14:28:08Z
dc.date.available2021-01-19T14:28:08Z
dc.date.issued2020
dc.description.abstractDNA intelligence, and particularly the inference of biogeographical ancestry (BGA) is increasing in interest, and relevance within the forensic genetics community. The majority of current MPS-based forensic ancestry-informative assays focus on the differentiation of major global populations. The recently published MAPlex (Multiplex for the Asia Pacific) panel contains 144 SNPs and 20 microhaplotypes and aims to improve the differentiation of populations in the Asia Pacific region. This study reports the first forensic evaluation of the MAPlex panel using AmpliSeq technology and Ion S5 sequencing. This study reports on the overall performance of MAPlex including the assay’s sequence coverage distribution and stability, baseline noise and description of problematic SNPs. Dilution series, artificially degraded and mixed DNA samples were also analysed to evaluate the sensitivity of the panel with challenging or compromised forensic samples. As the first panel to combine biallelic SNPs, multiple-allele SNPs and microhaplotypes, the MAPlex assay demonstrated an enhanced capacity for mixture detection, not easily performed with common binary SNPs. This performance evaluation indicates that MAPlex is a robust, stable and highly sensitive assay that is applicable to forensic casework for the prediction of BGAgl
dc.description.peerreviewedSIgl
dc.description.sponsorshipMdlP is supported by a postdoctoral fellowship awarded by the Consellería de Cultura, Educación e Ordenación Universitaria and the Consellería de Economía, Emprego e Industria from Xunta de Galicia (Modalidade A, ED481B 2017/088). CP, AFA, AMM, MdlP, MVL are supported by MAPA, Multiple Allele Polymorphism Analysis (BIO2016-78525-R), a research project funded by the Spanish Research State Agency (AEI), and co-financed with ERDF funds. AFA is supported by a post-doctorate grant funded by the Consellería de Cultura, Educación e Ordenación Universitaria e da Consellería de Economía, Emprego e Industria from Xunta de Galicia, Spain (Modalidade B, ED481B 2018/010). The 1000 Genomes high coverage sequence data were generated at the New York Genome Center with funds provided by NHGRI Grant 3UM1HG008901-03S1gl
dc.identifier.citationForensic Science International: Genetics, Volume 48, September 2020, 102344gl
dc.identifier.doi10.1016/j.fsigen.2020.102344
dc.identifier.issn1872-4973
dc.identifier.urihttp://hdl.handle.net/10347/24242
dc.language.isoenggl
dc.publisherElseviergl
dc.relation.publisherversionhttps://doi.org/10.1016/j.fsigen.2020.102344gl
dc.rights© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)gl
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional
dc.rights.accessRightsopen accessgl
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBiogeographical ancestry estimationgl
dc.subjectAsia-Pacific populationsgl
dc.subjectMassive parallel sequencinggl
dc.subjectIon S5 sequencinggl
dc.titleForensic evaluation of the Asia Pacific ancestry-informative MAPlex assaygl
dc.typejournal articlegl
dc.type.hasVersionVoRgl
dspace.entity.typePublication
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relation.isAuthorOfPublication6320e31a-29c8-47b5-8c8b-f234200cf297
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relation.isAuthorOfPublication.latestForDiscovery01f310f5-a326-4d6e-9656-0034b67a41a0

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