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Body fluid identification and assignment to donors using a targeted mRNA massively parallel sequencing approach – results of a second EUROFORGEN / EDNAP collaborative exercise


Ingold, Sabrina; Dørum, Guro; Hanson, Erin K; Ballard, David; Berti, Andrea; Gettings, Katherine Butler; Giangasparo, Federica; Kampmann, Marie-Louise; Laurent, François Xavier; Morling, Niels; Parson, Walther; Steffen, Carolyn R; Ulus, A; van den Berge, Margreet; van der Gaag, Kristian J; Verdoliva, Vincenzo; Xavier, Catarina; Ballantyne, J; Haas, Cordula (2020). Body fluid identification and assignment to donors using a targeted mRNA massively parallel sequencing approach – results of a second EUROFORGEN / EDNAP collaborative exercise. Forensic Science International. Genetics, 45:102208.

Abstract

In a previous EUROFORGEN/EDNAP collaborative exercise, we tested two assays for targeted mRNA massively parallel sequencing for the identification of body fluids/tissues, optimized for the Illumina MiSeq/FGx and the Ion Torrent PGM/S5 platforms, respectively. The task of the second EUROFORGEN/EDNAP collaborative exercise was to analyze dried body fluid stains with two different multiplexes, the former Illumina 33plex mRNA panel for body fluid/tissue identification and a 35plex cSNP panel for assignment of body fluids/tissues to donors that was introduced in a proof-of-concept study recently. The coding region SNPs (cSNPs) are located within the body fluid specific mRNA transcripts and represent a direct link between the body fluid and the donor. We predicted the origin of the stains using a partial least squares discriminant analysis (PLS-DA) model, where most of the single source samples were correctly predicted. The mixed body fluid stains showed poorer results, however, at least one component was predicted correctly in most stains. The cSNP data demonstrated that coding region SNPs can give valuable information on linking body fluids/tissues with donors in mixed body fluid stains. However, due to the unfavorable performance of some cSNPs, the interpretation remains challenging. As a consequence, additional markers are needed to increase the discrimination power in each body fluid/tissue category.

Abstract

In a previous EUROFORGEN/EDNAP collaborative exercise, we tested two assays for targeted mRNA massively parallel sequencing for the identification of body fluids/tissues, optimized for the Illumina MiSeq/FGx and the Ion Torrent PGM/S5 platforms, respectively. The task of the second EUROFORGEN/EDNAP collaborative exercise was to analyze dried body fluid stains with two different multiplexes, the former Illumina 33plex mRNA panel for body fluid/tissue identification and a 35plex cSNP panel for assignment of body fluids/tissues to donors that was introduced in a proof-of-concept study recently. The coding region SNPs (cSNPs) are located within the body fluid specific mRNA transcripts and represent a direct link between the body fluid and the donor. We predicted the origin of the stains using a partial least squares discriminant analysis (PLS-DA) model, where most of the single source samples were correctly predicted. The mixed body fluid stains showed poorer results, however, at least one component was predicted correctly in most stains. The cSNP data demonstrated that coding region SNPs can give valuable information on linking body fluids/tissues with donors in mixed body fluid stains. However, due to the unfavorable performance of some cSNPs, the interpretation remains challenging. As a consequence, additional markers are needed to increase the discrimination power in each body fluid/tissue category.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute of Legal Medicine
Dewey Decimal Classification:340 Law
610 Medicine & health
510 Mathematics
Scopus Subject Areas:Health Sciences > Pathology and Forensic Medicine
Life Sciences > Genetics
Uncontrolled Keywords:Pathology and Forensic Medicine, Genetics
Language:English
Date:1 March 2020
Deposited On:21 Jan 2020 14:40
Last Modified:22 Apr 2020 22:40
Publisher:Elsevier
ISSN:1872-4973
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.fsigen.2019.102208
PubMed ID:31869731

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