Impact of SNP microarray analysis of compromised DNA on kinship classification success in the context of investigative genetic genealogy

Jard H. de Vries, Daniel Kling, Athina Vidaki, Pascal Arp, Vivian Kalamara, Michael M.P.J. Verbiest, Danuta Piniewska-Róg, Thomas J. Parsons, André G. Uitterlinden, Manfred Kayser*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Single nucleotide polymorphism (SNP) data generated with microarray technologies have been used to solve murder cases via investigative leads obtained from identifying relatives of the unknown perpetrator included in accessible genomic databases, an approach referred to as investigative genetic genealogy (IGG). However, SNP microarrays were developed for relatively high input DNA quantity and quality, while DNA typically obtainable from crime scene stains is of low DNA quantity and quality, and SNP microarray data obtained from compromised DNA are largely missing. By applying the Illumina Global Screening Array (GSA) to 264 DNA samples with systematically altered quantity and quality, we empirically tested the impact of SNP microarray analysis of compromised DNA on kinship classification success, as relevant in IGG. Reference data from manufacturer-recommended input DNA quality and quantity were used to estimate genotype accuracy in the compromised DNA samples and for simulating data of different degree relatives. Although stepwise decrease of input DNA amount from 200 ng to 6.25 pg led to decreased SNP call rates and increased genotyping errors, kinship classification success did not decrease down to 250 pg for siblings and 1st cousins, 1 ng for 2nd cousins, while at 25 pg and below kinship classification success was zero. Stepwise decrease of input DNA quality via increased DNA fragmentation resulted in the decrease of genotyping accuracy as well as kinship classification success, which went down to zero at the average DNA fragment size of 150 base pairs. Combining decreased DNA quantity and quality in mock casework and skeletal samples further highlighted possibilities and limitations. Overall, GSA analysis achieved maximal kinship classification success from 800 to 200 times lower input DNA quantities than manufacturer-recommended, although DNA quality plays a key role too, while compromised DNA produced false negative kinship classifications rather than false positive ones.

Original languageEnglish
Article number102625
JournalForensic Science International: Genetics
Volume56
Early online date1 Nov 2021
DOIs
Publication statusPublished - 1 Jan 2022

Bibliographical note

Funding Information:
The work of J.H.V. P.A. M.V. A.G.U. A.V. V.K. M.K. was supported by Erasmus MC, University Medical Center Rotterdam. AV was additionally supported with an EUR Fellowship by Erasmus University Rotterdam. We thank Benjamin Planterose Jim?nez (Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam) for providing technical assistance and suggestions in implementing R, and Wojciech Branicki (Malopolska Centre of Biotechnology, Jagiellonian University) for his assistance with making bone DNA samples available to this study.

Funding Information:
The work of J.H.V., P.A., M.V., A.G.U., A.V., V.K., M.K. was supported by Erasmus MC, University Medical Center Rotterdam . AV was additionally supported with an EUR Fellowship by Erasmus University Rotterdam . We thank Benjamin Planterose Jiménez (Department of Genetic Identification, Erasmus MC, University Medical Center Rotterdam) for providing technical assistance and suggestions in implementing R, and Wojciech Branicki (Malopolska Centre of Biotechnology, Jagiellonian University) for his assistance with making bone DNA samples available to this study.

Publisher Copyright:
© 2021 The Authors

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