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HIrisPlex-S system for eye, hair, and skin color prediction from DNA: Massively parallel sequencing solutions for two common forensically used platforms

Breslin, Krystal; Wills, Bailey; Ralf, Arwin; Ventayol Garcia, Marina; Kukla-Bartoszek, Magdalena; Pośpiech, Ewelina; Freire-Aradas, Ana; Xavier, Catarina; Ingold, Sabrina; de La Puente, Maria; van der Gaag, Kristiaan J; Herrick, Noah; Haas, Cordula; Parson, Walther; Phillips, Christopher; Sijen, Titia; Branicki, Wojciech; Walsh, Susas; Kayser, Manfred (2019). HIrisPlex-S system for eye, hair, and skin color prediction from DNA: Massively parallel sequencing solutions for two common forensically used platforms. Forensic Science International. Genetics, 43:102152.

Abstract

Forensic DNA Phenotyping (FDP) provides the ability to predict externally visible characteristics from minute amounts of crime scene DNA, which can help find unknown perpetrators who are typically unidentifiable via conventional forensic DNA profiling. Fundamental human genetics research has led to a better understanding of the specific DNA variants responsible for physical appearance characteristics, particularly eye, hair, and skin color. Recently, we introduced the HIrisPlex-S system for the simultaneous prediction of eye, hair, and skin color based on 41 DNA variants generated from two forensically validated SNaPshot multiplex assays using capillary electrophoresis (CE). Here we introduce massively parallel sequencing (MPS) solutions for the HIrisPlex-S (HPS) system on two MPS platforms commonly used in forensics, Ion Torrent and MiSeq, that cover all 41 DNA variants in a single assay, respectively. Additionally, we present the forensic developmental validation of the two HPS-MPS assays. The Ion Torrent MPS assay, based on Ion AmpliSeq technology, illustrated the successful generation of full HIrisPlex-S genotypic profiles from 100 pg of input control DNA, while the MiSeq MPS assay based on an in-house design yielded complete profiles from 250 pg of input DNA. Assessing simulated forensic casework samples such as saliva, hair (bulb), blood, semen, and low quantity touch DNA, as well as artificially damaged DNA samples, concordance testing, and samples from numerous species, all illustrated the ability of both versions of the HIrisPlex-S MPS assay to produce results that motivate forensic applications. By also providing an integrated bioinformatics analysis pipeline, MPS data can now be analyzed and a file generated for upload to the publically accessible HIrisPlex online webtool (https://hirisplex.erasmusmc.nl). In addition, we updated the website to accept VCF input data for those with genome sequence data. We thus provide a user-friendly and semi-automated MPS workflow from DNA sample to individual eye, hair, and skin color prediction probabilities. Furthermore, we present a 2-person mixture separation tool that not only assesses genotype reliability with regards genotyping confidence but also provides the most fitting mixture scenario for both minor and major contributors, including profile separation. We envision this MPS implementation of the HIrisPlex-S system for eye, hair, and skin color prediction from DNA as a starting point for further expanding MPS-based forensic DNA phenotyping. This may include the future addition of SNPs predictive for more externally visible characteristics, as well as SNPs for bio-geographic ancestry inference, provided the statistical framework for DNA prediction of these traits is in place.

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 November 2019
Deposited On:16 Dec 2019 11:18
Last Modified:03 Sep 2024 03:38
Publisher:Elsevier
ISSN:1872-4973
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.fsigen.2019.102152
PubMed ID:31518964

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