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

Author(s):  
Jard H. de Vries ◽  
Daniel Kling ◽  
Athina Vidaki ◽  
Pascal Arp ◽  
Vivian Kalamara ◽  
...  
2021 ◽  
Author(s):  
Jard Hemmo de Vries ◽  
Daniel Kling ◽  
Athina Vidaki ◽  
Pascal Arp ◽  
Vivian Kalamara ◽  
...  

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, referred to as investigative genetic genealogy (IGG). However, SNP microarrays were developed for relatively high input DNA quantity and quality, while SNP microarray data from compromised DNA typically obtainable from crime scene stains 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 deprecated 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 nanogram to 6.25 picogram led to decreased SNP call rates and increased genotyping errors, kinship classification success did not decrease down to 250 picogram for siblings and 1st cousins, 1 nanogram for 2nd cousins, while at 25 picogram 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 800-200 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.


2014 ◽  
Vol 207 (6) ◽  
pp. 289-290
Author(s):  
A. Yenamandra ◽  
F.C. Wheeler ◽  
A.B. Hollis ◽  
L. Barba ◽  
Y. Wang ◽  
...  

2020 ◽  
Vol 47 ◽  
pp. 102293
Author(s):  
Sohee Cho ◽  
Moon-Young Kim ◽  
Ji Hyun Lee ◽  
Hwan Young Lee ◽  
Soong Deok Lee

Author(s):  
Ruth B. Lathi ◽  
Jamie A. M. Massie ◽  
Megan Loring ◽  
Zachary P. Demko ◽  
David Johnson ◽  
...  

2008 ◽  
Vol 30 (6) ◽  
pp. 507-507
Author(s):  
Ralph Melcher ◽  
Waltraud Zopf ◽  
Elena Hartmann ◽  
Andreas Rosenwald ◽  
Holger Hoehn ◽  
...  

2017 ◽  
Vol 214-215 ◽  
pp. 42-43
Author(s):  
Nadine Berry ◽  
Rodney Scott ◽  
Rosemary Sutton ◽  
Toby Trahair ◽  
Philip Rowlings ◽  
...  

2005 ◽  
Vol 117 (4) ◽  
pp. 389-397 ◽  
Author(s):  
Michael Wirtenberger ◽  
Kari Hemminki ◽  
Bowang Chen ◽  
Barbara Burwinkel

2012 ◽  
Vol 15 (1) ◽  
pp. 70-78 ◽  
Author(s):  
Kristen Lipscomb Sund ◽  
Sarah L. Zimmerman ◽  
Cameron Thomas ◽  
Anna L. Mitchell ◽  
Carlos E. Prada ◽  
...  

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