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Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms

We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined “index of chromosome sharing” (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of t...

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Autores principales: Morimoto, Chie, Manabe, Sho, Kawaguchi, Takahisa, Kawai, Chihiro, Fujimoto, Shuntaro, Hamano, Yuya, Yamada, Ryo, Matsuda, Fumihiko, Tamaki, Keiji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966930/
https://www.ncbi.nlm.nih.gov/pubmed/27472558
http://dx.doi.org/10.1371/journal.pone.0160287
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author Morimoto, Chie
Manabe, Sho
Kawaguchi, Takahisa
Kawai, Chihiro
Fujimoto, Shuntaro
Hamano, Yuya
Yamada, Ryo
Matsuda, Fumihiko
Tamaki, Keiji
author_facet Morimoto, Chie
Manabe, Sho
Kawaguchi, Takahisa
Kawai, Chihiro
Fujimoto, Shuntaro
Hamano, Yuya
Yamada, Ryo
Matsuda, Fumihiko
Tamaki, Keiji
author_sort Morimoto, Chie
collection PubMed
description We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined “index of chromosome sharing” (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from first- to fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., ≥ 10(8)); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability ≥ 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons.
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spelling pubmed-49669302016-08-18 Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms Morimoto, Chie Manabe, Sho Kawaguchi, Takahisa Kawai, Chihiro Fujimoto, Shuntaro Hamano, Yuya Yamada, Ryo Matsuda, Fumihiko Tamaki, Keiji PLoS One Research Article We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined “index of chromosome sharing” (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from first- to fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., ≥ 10(8)); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability ≥ 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons. Public Library of Science 2016-07-29 /pmc/articles/PMC4966930/ /pubmed/27472558 http://dx.doi.org/10.1371/journal.pone.0160287 Text en © 2016 Morimoto et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Morimoto, Chie
Manabe, Sho
Kawaguchi, Takahisa
Kawai, Chihiro
Fujimoto, Shuntaro
Hamano, Yuya
Yamada, Ryo
Matsuda, Fumihiko
Tamaki, Keiji
Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title_full Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title_fullStr Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title_full_unstemmed Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title_short Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms
title_sort pairwise kinship analysis by the index of chromosome sharing using high-density single nucleotide polymorphisms
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4966930/
https://www.ncbi.nlm.nih.gov/pubmed/27472558
http://dx.doi.org/10.1371/journal.pone.0160287
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