Literature DB >> 34753062

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

Jard H de Vries1, Daniel Kling2, Athina Vidaki3, Pascal Arp1, Vivian Kalamara3, Michael M P J Verbiest1, Danuta Piniewska-Róg4, Thomas J Parsons5, André G Uitterlinden6, Manfred Kayser7.   

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.
Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Compromised DNA; Forensic genetics; Investigative genetic genealogy; Kinship classification; Relative identification; SNP microarray

Mesh:

Substances:

Year:  2021        PMID: 34753062     DOI: 10.1016/j.fsigen.2021.102625

Source DB:  PubMed          Journal:  Forensic Sci Int Genet        ISSN: 1872-4973            Impact factor:   4.882


  3 in total

1.  Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples.

Authors:  Stephen D Turner; V P Nagraj; Matthew Scholz; Shakeel Jessa; Carlos Acevedo; Jianye Ge; August E Woerner; Bruce Budowle
Journal:  Front Genet       Date:  2022-06-30       Impact factor: 4.772

Review 2.  Forensic genetics through the lens of Lewontin: population structure, ancestry and race.

Authors:  Mark A Jobling
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2022-04-18       Impact factor: 6.671

3.  A machine learning approach for missing persons cases with high genotyping errors.

Authors:  Meng Huang; Muyi Liu; Hongmin Li; Jonathan King; Amy Smuts; Bruce Budowle; Jianye Ge
Journal:  Front Genet       Date:  2022-10-03       Impact factor: 4.772

  3 in total

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