Building a custom large-scale panel of novel microhaplotypes for forensic identification using MiSeq and Ion S5 massively parallel sequencing systems
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Puente Vila, María del Carmen de la
Carracedo Álvarez, Ángel
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Elsevier
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A large number of new microhaplotype loci were identified in the human genome by applying a directed search with selection criteria emphasizing short haplotype length (<120 nucleotides) and maximum levels of polymorphism in the composite SNPs. From these searches, 107 autosomal microhaplotypes and 11 X chromosome microhaplotypes were selected, with well-spaced autosomal positions to ensure their independence in relationship tests. The 118 microhaplotypes were assembled into a single multiplex assay for the analysis of forensic DNA with massively parallel sequencing (MPS). A single AmpliSeq-adapted primer set was made for Illumina MiSeq and Thermo Fisher Ion S5 MPS platforms and the performance of the assay was comprehensively evaluated in both systems. Five microhaplotypes showed critical sequencing failures in both MPS platforms and were removed, while a further 13 required manual checks and the application of sequence quality thresholds in one or both systems to ensure the successful analysis of low-level DNA in these loci. The targeting of short microhaplotype spans during marker selection, with an average length of 51 nucleotides in the 118 loci, led to a high level of sensitivity for the panel when sequencing the very degraded DNA typically encountered in forensic casework and the identification of missing persons
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Forensic Science International: Genetics, Volume 45, March 2020, 102213
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https://doi.org/10.1016/j.fsigen.2019.102213Sponsors
The studies reported and authors MdlP, CP, 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. MdlP is supported by a postdoctoral fellowship awarded 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 studies reported have received funding 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
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© 2019 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/)
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