Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples
Technological 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 gen...
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| Format: | Article |
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Frontiers Media S.A.
2022-06-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.882268/full |
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| author | Stephen D. Turner V.P. Nagraj Matthew Scholz Shakeel Jessa Carlos Acevedo Jianye Ge Jianye Ge August E. Woerner August E. Woerner Bruce Budowle Bruce Budowle |
| author_facet | Stephen D. Turner V.P. Nagraj Matthew Scholz Shakeel Jessa Carlos Acevedo Jianye Ge Jianye Ge August E. Woerner August E. Woerner Bruce Budowle Bruce Budowle |
| author_sort | Stephen D. Turner |
| collection | DOAJ |
| description | Technological 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. |
| first_indexed | 2024-12-12T08:31:21Z |
| format | Article |
| id | doaj.art-40fa3610553b4d89a797fb3d67e97e95 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-12T08:31:21Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-40fa3610553b4d89a797fb3d67e97e952022-12-22T00:31:05ZengFrontiers Media S.A.Frontiers in Genetics1664-80212022-06-011310.3389/fgene.2022.882268882268Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic SamplesStephen D. Turner0V.P. Nagraj1Matthew Scholz2Shakeel Jessa3Carlos Acevedo4Jianye Ge5Jianye Ge6August E. Woerner7August E. Woerner8Bruce Budowle9Bruce Budowle10Signature Science, LLC., Austin, TX, United StatesSignature Science, LLC., Austin, TX, United StatesSignature Science, LLC., Austin, TX, United StatesSignature Science, LLC., Austin, TX, United StatesSignature Science, LLC., Austin, TX, United StatesCenter for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, United StatesDepartment of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, United StatesCenter for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, United StatesDepartment of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, United StatesCenter for Human Identification, University of North Texas Health Science Center, Fort Worth, TX, United StatesDepartment of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, Fort Worth, TX, United StatesTechnological 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.https://www.frontiersin.org/articles/10.3389/fgene.2022.882268/fullSNPkinshipforensicsgenealogyforensic genetic genealogyrelatedness |
| spellingShingle | Stephen D. Turner V.P. Nagraj Matthew Scholz Shakeel Jessa Carlos Acevedo Jianye Ge Jianye Ge August E. Woerner August E. Woerner Bruce Budowle Bruce Budowle Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples Frontiers in Genetics SNP kinship forensics genealogy forensic genetic genealogy relatedness |
| title | Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples |
| title_full | Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples |
| title_fullStr | Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples |
| title_full_unstemmed | Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples |
| title_short | Evaluating the Impact of Dropout and Genotyping Error on SNP-Based Kinship Analysis With Forensic Samples |
| title_sort | evaluating the impact of dropout and genotyping error on snp based kinship analysis with forensic samples |
| topic | SNP kinship forensics genealogy forensic genetic genealogy relatedness |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.882268/full |
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