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MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes

A major challenge in zooarchaeology is to morphologically distinguish closely related species’ remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species’ reference genomes will only apply when reference nucle...

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Autores principales: Atağ, Gözde, Vural, Kıvılcım Başak, Kaptan, Damla, Özkan, Mustafa, Koptekin, Dilek, Sağlıcan, Ekin, Doğramacı, Sevcan, Köz, Mevlüt, Yılmaz, Ardan, Söylev, Arda, Togan, İnci, Somel, Mehmet, Özer, Füsun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: F1000 Research Limited 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10565424/
https://www.ncbi.nlm.nih.gov/pubmed/37829208
http://dx.doi.org/10.12688/openreseurope.14936.3
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author Atağ, Gözde
Vural, Kıvılcım Başak
Kaptan, Damla
Özkan, Mustafa
Koptekin, Dilek
Sağlıcan, Ekin
Doğramacı, Sevcan
Köz, Mevlüt
Yılmaz, Ardan
Söylev, Arda
Togan, İnci
Somel, Mehmet
Özer, Füsun
author_facet Atağ, Gözde
Vural, Kıvılcım Başak
Kaptan, Damla
Özkan, Mustafa
Koptekin, Dilek
Sağlıcan, Ekin
Doğramacı, Sevcan
Köz, Mevlüt
Yılmaz, Ardan
Söylev, Arda
Togan, İnci
Somel, Mehmet
Özer, Füsun
author_sort Atağ, Gözde
collection PubMed
description A major challenge in zooarchaeology is to morphologically distinguish closely related species’ remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species’ reference genomes will only apply when reference nuclear genomes of comparable quality are available, and may still fail when coverages are low. Here, we propose an alternative method, MTaxi, that uses highly accessible mitochondrial DNA (mtDNA) to distinguish between pairs of closely related species from ancient DNA sequences. MTaxi utilises mtDNA transversion-type substitutions between pairs of candidate species, assigns reads to either species, and performs a binomial test to determine the sample taxon. We tested MTaxi on sheep/goat and horse/donkey data, between which zooarchaeological classification can be challenging in ways that epitomise our case. The method performed efficiently on simulated ancient genomes down to 0.3x mitochondrial coverage for both sheep/goat and horse/donkey, with no false positives. Trials on n=18 ancient sheep/goat samples and n=10 horse/donkey samples of known species identity also yielded 100% accuracy. Overall, MTaxi provides a straightforward approach to classify closely related species that are difficult to distinguish through zooarchaeological methods using low coverage aDNA data, especially when similar quality reference genomes are unavailable. MTaxi is freely available at https://github.com/goztag/MTaxi.
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spelling pubmed-105654242023-10-12 MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes Atağ, Gözde Vural, Kıvılcım Başak Kaptan, Damla Özkan, Mustafa Koptekin, Dilek Sağlıcan, Ekin Doğramacı, Sevcan Köz, Mevlüt Yılmaz, Ardan Söylev, Arda Togan, İnci Somel, Mehmet Özer, Füsun Open Res Eur Software Tool Article A major challenge in zooarchaeology is to morphologically distinguish closely related species’ remains, especially using small bone fragments. Shotgun sequencing aDNA from archeological remains and comparative alignment to the candidate species’ reference genomes will only apply when reference nuclear genomes of comparable quality are available, and may still fail when coverages are low. Here, we propose an alternative method, MTaxi, that uses highly accessible mitochondrial DNA (mtDNA) to distinguish between pairs of closely related species from ancient DNA sequences. MTaxi utilises mtDNA transversion-type substitutions between pairs of candidate species, assigns reads to either species, and performs a binomial test to determine the sample taxon. We tested MTaxi on sheep/goat and horse/donkey data, between which zooarchaeological classification can be challenging in ways that epitomise our case. The method performed efficiently on simulated ancient genomes down to 0.3x mitochondrial coverage for both sheep/goat and horse/donkey, with no false positives. Trials on n=18 ancient sheep/goat samples and n=10 horse/donkey samples of known species identity also yielded 100% accuracy. Overall, MTaxi provides a straightforward approach to classify closely related species that are difficult to distinguish through zooarchaeological methods using low coverage aDNA data, especially when similar quality reference genomes are unavailable. MTaxi is freely available at https://github.com/goztag/MTaxi. F1000 Research Limited 2023-09-29 /pmc/articles/PMC10565424/ /pubmed/37829208 http://dx.doi.org/10.12688/openreseurope.14936.3 Text en Copyright: © 2023 Atağ G et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Software Tool Article
Atağ, Gözde
Vural, Kıvılcım Başak
Kaptan, Damla
Özkan, Mustafa
Koptekin, Dilek
Sağlıcan, Ekin
Doğramacı, Sevcan
Köz, Mevlüt
Yılmaz, Ardan
Söylev, Arda
Togan, İnci
Somel, Mehmet
Özer, Füsun
MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title_full MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title_fullStr MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title_full_unstemmed MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title_short MTaxi: A comparative tool for taxon identification of ultra low coverage ancient genomes
title_sort mtaxi: a comparative tool for taxon identification of ultra low coverage ancient genomes
topic Software Tool Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10565424/
https://www.ncbi.nlm.nih.gov/pubmed/37829208
http://dx.doi.org/10.12688/openreseurope.14936.3
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