Title

Body Fluid Identification Using A Targeted Mrna Massively Parallel Sequencing Approach – Results Of A Euroforgen/Ednap Collaborative Exercise

Keywords

Body fluid identification; Forensic science; Massively parallel sequencing; mRNA profiling

Abstract

In a previous study we presented an assay for targeted mRNA sequencing for the identification of human body fluids, optimised for the Illumina MiSeq/FGx MPS platform. This assay, together with an additional in-house designed assay for the Ion Torrent PGM/S5 platform, was the basis for a collaborative exercise within 17 EUROFORGEN and EDNAP laboratories, in order to test the efficacy of targeted mRNA sequencing to identify body fluids. The task was to analyse the supplied dried body fluid stains and, optionally, participants’ own bona fide or mock casework samples of human origin, according to specified protocols. The provided primer pools for the Illumina MiSeq/FGx and the Ion Torrent PGM/S5 platforms included 33 and 29 body fluid specific targets, respectively, to identify blood, saliva, semen, vaginal secretion, menstrual blood and skin. The results demonstrated moderate to high count values in the body fluid or tissue of interest with little to no counts in non-target body fluids. There was some inter-laboratory variability in read counts, but overall the results of the laboratories were comparable in that highly expressed markers showed high read counts and less expressed markers showed lower counts. We performed a partial least squares (PLS) analysis on the data, where blood, menstrual blood, saliva and semen markers and samples clustered well. The results of this collaborative mRNA massively parallel sequencing (MPS) exercise support targeted mRNA sequencing as a reliable body fluid identification method that could be added to the repertoire of forensic MPS panels.

Publication Date

5-1-2018

Publication Title

Forensic Science International: Genetics

Volume

34

Number of Pages

105-115

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.fsigen.2018.01.002

Socpus ID

85042184724 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85042184724

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