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Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations

The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is...

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Autores principales: Das, Ranajit, Roy, Ria, Venkatesh, Neha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375890/
https://www.ncbi.nlm.nih.gov/pubmed/30800141
http://dx.doi.org/10.3389/fgene.2019.00043
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author Das, Ranajit
Roy, Ria
Venkatesh, Neha
author_facet Das, Ranajit
Roy, Ria
Venkatesh, Neha
author_sort Das, Ranajit
collection PubMed
description The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is largely unknown, which has constrained management of captive gorillas aiming at maximizing genetic diversity at the population level. In recent years, ancestry informative markers (AIMs) has been successfully employed for the inference of genomic ancestry in a wide range of studies in evolutionary genetics, biomedical research, genetic stock identification, and introgression analysis and forensic analyses. In this study, we sought to derive the AIMs yielding the most cohesive and faithful understanding of biogeographical affiliation of query gorillas. To this end, we compared three commonly used AIMs-determining methods namely, Infocalc, F(ST), and Smart Principal Component Analysis (SmartPCA) with ADMIXTURE, using gorilla genome data available through Great Ape Genome Project database. Our findings suggest that the SNPs that were detected by at least three of the four AIMs-determining approaches (N = 1,531), is likely most suitable for delineation of gorilla AIMs. It recapitulated the finer structure within western lowland gorilla genomes with high degree of precision. We further have validated the robustness of our results using a randomized negative control containing the same number of SNPs. To the best of our knowledge, this is the first report of an AIMs panel for gorillas that may aid in developing cost-effective resources for large-scale demographic analyses, and greatly help in conservation of this charismatic mega-fauna.
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spelling pubmed-63758902019-02-22 Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations Das, Ranajit Roy, Ria Venkatesh, Neha Front Genet Genetics The knowledge of ancestral origin is monumental in conservation of endangered animals since it can aid in preservation of population level genetic integrity and prevent inbreeding among related individuals. Despite maintenance of studbook, the biogeographical affiliation of most captive gorillas is largely unknown, which has constrained management of captive gorillas aiming at maximizing genetic diversity at the population level. In recent years, ancestry informative markers (AIMs) has been successfully employed for the inference of genomic ancestry in a wide range of studies in evolutionary genetics, biomedical research, genetic stock identification, and introgression analysis and forensic analyses. In this study, we sought to derive the AIMs yielding the most cohesive and faithful understanding of biogeographical affiliation of query gorillas. To this end, we compared three commonly used AIMs-determining methods namely, Infocalc, F(ST), and Smart Principal Component Analysis (SmartPCA) with ADMIXTURE, using gorilla genome data available through Great Ape Genome Project database. Our findings suggest that the SNPs that were detected by at least three of the four AIMs-determining approaches (N = 1,531), is likely most suitable for delineation of gorilla AIMs. It recapitulated the finer structure within western lowland gorilla genomes with high degree of precision. We further have validated the robustness of our results using a randomized negative control containing the same number of SNPs. To the best of our knowledge, this is the first report of an AIMs panel for gorillas that may aid in developing cost-effective resources for large-scale demographic analyses, and greatly help in conservation of this charismatic mega-fauna. Frontiers Media S.A. 2019-02-08 /pmc/articles/PMC6375890/ /pubmed/30800141 http://dx.doi.org/10.3389/fgene.2019.00043 Text en Copyright © 2019 Das, Roy and Venkatesh. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Das, Ranajit
Roy, Ria
Venkatesh, Neha
Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title_full Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title_fullStr Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title_full_unstemmed Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title_short Using Ancestry Informative Markers (AIMs) to Detect Fine Structures Within Gorilla Populations
title_sort using ancestry informative markers (aims) to detect fine structures within gorilla populations
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375890/
https://www.ncbi.nlm.nih.gov/pubmed/30800141
http://dx.doi.org/10.3389/fgene.2019.00043
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