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Investigative genetic genealogy : Current methods, knowledge and practice

Daniel Kling (Författare), Christopher Phillips (Författare), Debbie Kennett (Författare), Andreas Tillmar (Författare)

URI http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175404, URN urn:nbn:se:liu:diva-175404, DOI 10.1016/j.fsigen.2021.102474

Linköpings universitet Institutionen för biomedicinska och kliniska vetenskaper (Utgivare), Linköpings universitet Medicinska fakulteten (Utgivare)

utgivning

Elsevier Ireland Ltd, 2021

är del av

Forensic Science International · ISSN 1872-4973

Bidrag, Onlineresurs

Finns online:

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175404

Värdpublikation

ämne

Natural Sciences, Biological Sciences, Genetics, Naturvetenskap, Biologi, Genetik, Genetic genealogy; SNP microarrays; Whole-genome-sequencing; Familial searching; Identity by descent; Forensic DNA analysis; Crime investigation

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Sammanfattning

Investigative genetic genealogy (IGG) has emerged as a new, rapidly growing field of forensic science. We describe the process whereby dense SNP data, commonly comprising more than half a million markers, are employed to infer distant relationships. By distant we refer to degrees of relatedness exceeding that of first cousins. We review how methods of relationship matching and SNP analysis on an enlarged scale are used in a forensic setting to identify a suspect in a criminal investigation or a missing person. There is currently a strong need in forensic genetics not only to understand the underlying models to infer relatedness but also to fully explore the DNA technologies and data used in IGG. This review brings together many of the topics and examines their effectiveness and operational limits, while suggesting future directions for their forensic validation. We further investigated the methods used by the major direct-to-consumer (DTC) genetic ancestry testing companies as well as submitting a questionnaire where providers of forensic genetic genealogy summarized their operation/ services. Although most of the DTC market, and genetic genealogy in general, has undisclosed, proprietary algorithms we review the current knowledge where information has been discussed and published more openly.