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Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas
BACKGROUND: The utilization of high resolution genome data has important implications for the phylogeographical evaluation of non-human species. Biogeographical analyses can yield detailed understanding of their population biology and facilitate the geo-localization of individuals to promote their e...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362561/ https://www.ncbi.nlm.nih.gov/pubmed/30717677 http://dx.doi.org/10.1186/s12859-018-2568-5 |
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author | Das, Ranajit Upadhyai, Priyanka |
author_facet | Das, Ranajit Upadhyai, Priyanka |
author_sort | Das, Ranajit |
collection | PubMed |
description | BACKGROUND: The utilization of high resolution genome data has important implications for the phylogeographical evaluation of non-human species. Biogeographical analyses can yield detailed understanding of their population biology and facilitate the geo-localization of individuals to promote their efficacious management, particularly when bred in captivity. The Geographic Population Structure (GPS) algorithm is an admixture based tool for inference of biogeographical affinities and has been employed for the geo-localization of various human populations worldwide. Here, we applied the GPS tool for biogeographical analyses and localization of the ancestral origins of wild and captive gorilla genomes, of unknown geographic source, available in the Great Ape Genome Project (GAGP), employing Gorillas with known ancestral origin as the reference data. RESULTS: Our findings suggest that GPS was successful in recapitulating the population history and estimating the geographic origins of all gorilla genomes queried and localized the wild gorillas with unknown geographical origin < 150 km of National Parks/Wildlife Reserves within the political boundaries of countries, considered as prominent modern-day abode for gorillas in the wild. Further, the GPS localization of most captive-born gorillas was congruent with their previously presumed ancestral homes. CONCLUSIONS: Currently there is limited knowledge of the ancestral origins of most North American captive gorillas, and our study highlights the usefulness of GPS for inferring ancestry of captive gorillas. Determination of the native geographical source of captive gorillas can provide valuable information to guide breeding programs and ensure their appropriate management at the population level. Finally, our findings shine light on the broader applicability of GPS for protecting the genetic integrity of other endangered non-human species, where controlled breeding is a vital component of their conservation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2568-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6362561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63625612019-02-14 Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas Das, Ranajit Upadhyai, Priyanka BMC Bioinformatics Research BACKGROUND: The utilization of high resolution genome data has important implications for the phylogeographical evaluation of non-human species. Biogeographical analyses can yield detailed understanding of their population biology and facilitate the geo-localization of individuals to promote their efficacious management, particularly when bred in captivity. The Geographic Population Structure (GPS) algorithm is an admixture based tool for inference of biogeographical affinities and has been employed for the geo-localization of various human populations worldwide. Here, we applied the GPS tool for biogeographical analyses and localization of the ancestral origins of wild and captive gorilla genomes, of unknown geographic source, available in the Great Ape Genome Project (GAGP), employing Gorillas with known ancestral origin as the reference data. RESULTS: Our findings suggest that GPS was successful in recapitulating the population history and estimating the geographic origins of all gorilla genomes queried and localized the wild gorillas with unknown geographical origin < 150 km of National Parks/Wildlife Reserves within the political boundaries of countries, considered as prominent modern-day abode for gorillas in the wild. Further, the GPS localization of most captive-born gorillas was congruent with their previously presumed ancestral homes. CONCLUSIONS: Currently there is limited knowledge of the ancestral origins of most North American captive gorillas, and our study highlights the usefulness of GPS for inferring ancestry of captive gorillas. Determination of the native geographical source of captive gorillas can provide valuable information to guide breeding programs and ensure their appropriate management at the population level. Finally, our findings shine light on the broader applicability of GPS for protecting the genetic integrity of other endangered non-human species, where controlled breeding is a vital component of their conservation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-018-2568-5) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-05 /pmc/articles/PMC6362561/ /pubmed/30717677 http://dx.doi.org/10.1186/s12859-018-2568-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Das, Ranajit Upadhyai, Priyanka Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title | Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title_full | Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title_fullStr | Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title_full_unstemmed | Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title_short | Application of the geographic population structure (GPS) algorithm for biogeographical analyses of wild and captive gorillas |
title_sort | application of the geographic population structure (gps) algorithm for biogeographical analyses of wild and captive gorillas |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362561/ https://www.ncbi.nlm.nih.gov/pubmed/30717677 http://dx.doi.org/10.1186/s12859-018-2568-5 |
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