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

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dc.creatorTurner, Stephen D.
dc.creatorNagraj, V. P.
dc.creatorScholz, Matthew
dc.creatorJessa, Shakeel
dc.creatorAcevedo, Carlos
dc.creatorGe, Jianye
dc.creatorWoerner, August E.
dc.creatorBudowle, Bruce
dc.creator.orcid0000-0001-8724-075X (Ge, Jianye)
dc.creator.orcid0000-0002-9372-1127 (Woerner, August E.)
dc.date.accessioned2022-09-16T19:51:21Z
dc.date.available2022-09-16T19:51:21Z
dc.date.issued2022-06-30
dc.description.abstractTechnological advances in sequencing and single nucleotide polymorphism (SNP) genotyping microarray technology have facilitated advances in forensic analysis beyond short tandem repeat (STR) profiling, enabling the identification of unknown DNA samples and distant relationships. Forensic genetic genealogy (FGG) has facilitated the identification of distant relatives of both unidentified remains and unknown donors of crime scene DNA, invigorating the use of biological samples to resolve open cases. Forensic samples are often degraded or contain only trace amounts of DNA. In this study, the accuracy of genome-wide relatedness methods and identity by descent (IBD) segment approaches was evaluated in the presence of challenges commonly encountered with forensic data: missing data and genotyping error. Pedigree whole-genome simulations were used to estimate the genotypes of thousands of individuals with known relationships using multiple populations with different biogeographic ancestral origins. Simulations were also performed with varying error rates and types. Using these data, the performance of different methods for quantifying relatedness was benchmarked across these scenarios. When the genotyping error was low (<1%), IBD segment methods outperformed genome-wide relatedness methods for close relationships and are more accurate at distant relationship inference. However, with an increasing genotyping error (1-5%), methods that do not rely on IBD segment detection are more robust and outperform IBD segment methods. The reduced call rate had little impact on either class of methods. These results have implications for the use of dense SNP data in forensic genomics for distant kinship analysis and FGG, especially when the sample quality is low.
dc.description.sponsorshipThis work was supported in part by award 2019-DU-BX-0046 (Dense DNA Data for Enhanced Missing Persons Identification) to BB, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice and by internal funds from the Center for Human Identification. The opinions, findings, and conclusions or recommendations expressed are those of the authors and do not necessarily reflect those of the U.S. Department of Justice.
dc.identifier.citationTurner, S. D., Nagraj, V. P., Scholz, M., Jessa, S., Acevedo, C., Ge, J., Woerner, A. E., & Budowle, B. (2022). Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples. Frontiers in genetics, 13, 882268. https://doi.org/10.3389/fgene.2022.882268
dc.identifier.issn1664-8021
dc.identifier.urihttps://hdl.handle.net/20.500.12503/31758
dc.identifier.volume13
dc.publisherFrontiers Media S.A.
dc.relation.urihttps://doi.org/10.3389/fgene.2022.882268
dc.rights.holderCopyright © 2022 Turner, Nagraj, Scholz, Jessa, Acevedo, Ge, Woerner and Budowle
dc.rights.licenseAttribution 4.0 International (CC BY 4.0)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceFrontiers in Genetics
dc.subjectSnp
dc.subjectforensic genetic genealogy
dc.subjectforensics
dc.subjectgenealogy
dc.subjectkinship
dc.subjectrelatedness
dc.titleEvaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples
dc.typeArticle
dc.type.materialtext

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