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It's all relative: A multi-generational study using ForenSeq™ Kintelligence.
Daniel, R; Raymond, J; Sears, A; Stock, A; Scudder, N; Padmabandu, G; Kumar, S A; Snedecor, J; Antunes, J; Hartman, D.
Afiliación
  • Daniel R; Victorian Institute of Forensic Medicine, Victoria, Australia.
  • Raymond J; Forensic Evidence and Technical Services, New South Wales Police Force, Sydney, Australia.
  • Sears A; Forensic Evidence and Technical Services, New South Wales Police Force, Sydney, Australia.
  • Stock A; Victorian Institute of Forensic Medicine, Victoria, Australia.
  • Scudder N; Australian Federal Police, Canberra, Australian Capital Territory, Australia.
  • Padmabandu G; Qiagen HID LLC, Germantown, MD, United States.
  • Kumar SA; Qiagen HID LLC, Germantown, MD, United States.
  • Snedecor J; Qiagen HID LLC, Germantown, MD, United States.
  • Antunes J; Qiagen HID LLC, Germantown, MD, United States.
  • Hartman D; Victorian Institute of Forensic Medicine, Victoria, Australia; Department of Forensic Medicine, Monash University, Victoria, Australia. Electronic address: dadna.hartman@vifm.org.
Forensic Sci Int ; 364: 112208, 2024 Aug 27.
Article en En | MEDLINE | ID: mdl-39232402
ABSTRACT
The successful application of Forensic Investigative Genetic Genealogy (FIGG) to the identification of unidentified human remains and perpetrators of serious crime has led to a growing interest in its use internationally, including Australia. Routinely, FIGG has relied on the generation of high-density single nucleotide polymorphism (SNP) profiles from forensic samples using whole genome array (WGA) (∼650,000 or more SNPs) or whole genome sequencing (WGS) (millions of SNPs) for DNA segment-based comparisons in commercially available genealogy databases. To date, this approach has required DNA of a quality and quantity that is often not compatible with forensic samples. Furthermore, it requires the management of large data sets that include SNPs of medical relevance. The ForenSeq™ Kintelligence kit, comprising of 10,230 SNPs including 9867 for kinship association, was designed to overcome these challenges using a targeted amplicon sequencing-based method developed for low DNA inputs, inhibited and/or degraded forensic samples. To assess the ability of the ForenSeq™ Kintelligence workflow to correctly predict biological relationships, a comparative study comprising of 12 individuals from a family (with varying degrees of relatedness from 1st to 6th degree relatives) was undertaken using ForenSeq™ Kintelligence and a WGA approach using the Illumina Global Screening Array-24 version 3.0 Beadchip. All expected 1st, 2nd, 3rd, 4th and 5th degree relationships were correctly predicted using ForenSeq™ Kintelligence, while the expected 6th degree relationships were not detected. Given the (often) limited availability of forensic samples, findings from this study will assist Australian Law enforcement and other agencies considering the use of FIGG, to determine if the ForenSeq™ Kintelligence is suitable for existing workflows and casework sample types considered for FIGG.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Forensic Sci Int Año: 2024 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Forensic Sci Int Año: 2024 Tipo del documento: Article
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