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SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA
Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606150/ https://www.ncbi.nlm.nih.gov/pubmed/37895186 http://dx.doi.org/10.3390/genes14101837 |
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author | Köksal, Zehra Børsting, Claus Gusmão, Leonor Pereira, Vania |
author_facet | Köksal, Zehra Børsting, Claus Gusmão, Leonor Pereira, Vania |
author_sort | Köksal, Zehra |
collection | PubMed |
description | Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics. |
format | Online Article Text |
id | pubmed-10606150 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106061502023-10-28 SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA Köksal, Zehra Børsting, Claus Gusmão, Leonor Pereira, Vania Genes (Basel) Article Genetic variants on non-recombining DNA and the hierarchical order in which they accumulate are commonly of interest. This variant hierarchy can be established and combined with information on the population and geographic origin of the individuals carrying the variants to find population structures and infer migration patterns. Further, individuals can be assigned to the characterized populations, which is relevant in forensic genetics, genetic genealogy, and epidemiologic studies. However, there is currently no straightforward method to obtain such a variant hierarchy. Here, we introduce the software SNPtotree v1.0, which uniquely determines the hierarchical order of variants on non-recombining DNA without error-prone manual sorting. The algorithm uses pairwise variant comparisons to infer their relationships and integrates the combined information into a phylogenetic tree. Variants that have contradictory pairwise relationships or ambiguous positions in the tree are removed by the software. When benchmarked using two human Y-chromosomal massively parallel sequencing datasets, SNPtotree outperforms traditional methods in the accuracy of phylogenetic trees for sequencing data with high amounts of missing information. The phylogenetic trees of variants created using SNPtotree can be used to establish and maintain publicly available phylogeny databases to further explore genetic epidemiology and genealogy, as well as population and forensic genetics. MDPI 2023-09-22 /pmc/articles/PMC10606150/ /pubmed/37895186 http://dx.doi.org/10.3390/genes14101837 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Köksal, Zehra Børsting, Claus Gusmão, Leonor Pereira, Vania SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title | SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title_full | SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title_fullStr | SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title_full_unstemmed | SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title_short | SNPtotree—Resolving the Phylogeny of SNPs on Non-Recombining DNA |
title_sort | snptotree—resolving the phylogeny of snps on non-recombining dna |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606150/ https://www.ncbi.nlm.nih.gov/pubmed/37895186 http://dx.doi.org/10.3390/genes14101837 |
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