A comprehensive study of allele drop-in over an extended period of time.


Journal

Forensic science international. Genetics
ISSN: 1878-0326
Titre abrégé: Forensic Sci Int Genet
Pays: Netherlands
ID NLM: 101317016

Informations de publication

Date de publication:
09 2020
Historique:
received: 02 01 2019
revised: 22 05 2020
accepted: 04 06 2020
pubmed: 3 7 2020
medline: 13 7 2021
entrez: 3 7 2020
Statut: ppublish

Résumé

Some probabilistic mixture programmes take into account the presence of additional alleles by utilising drop-in models [1-4]. Although the precise details of the various models vary, at their core, they all rely on two basic assumptions - (1) that drop-in events occur independently of each other and (2) the frequency of individual dropped-in alleles mirrors the composition within some specified population. In order to examine the robustness of these assumptions, we have collected data on allele drop-in and contamination events in 28,842 negative control samples processed over a three year period in our DNA crime laboratory. These data were used to characterise drop-in events, and to identify trends in drop-in rates over time and between control types. In addition, we carried out an experiment using genomic DNA that had been highly diluted and demonstrate that, at these levels, drop-in events become indistinguishable from low level genomic contamination. Our results show that drop-in alleles are not necessarily independent random events. Moreover, a comparison between our data and UK frequency databases also suggests that the frequency of individual dropped-in alleles does not mirror the general population frequencies.

Identifiants

pubmed: 32615398
pii: S1872-4973(20)30105-8
doi: 10.1016/j.fsigen.2020.102332
pii:
doi:

Substances chimiques

DNA 9007-49-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102332

Informations de copyright

Copyright © 2020 Elsevier B.V. All rights reserved.

Auteurs

David Moore (D)

Eurofins Forensic Services, Teddington, UK. Electronic address: davidmoore@eurofins.co.uk.

Tim Clayton (T)

Eurofins Forensic Services, Wakefield, UK.

Jim Thomson (J)

Eurofins Forensic Services, Teddington, UK.

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Classifications MeSH