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Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives

Population genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene captur...

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Autores principales: Maisano Delser, Pierpaolo, Corrigan, Shannon, Hale, Matthew, Li, Chenhong, Veuille, Michel, Planes, Serge, Naylor, Gavin, Mona, Stefano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5030670/
https://www.ncbi.nlm.nih.gov/pubmed/27651217
http://dx.doi.org/10.1038/srep33753
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author Maisano Delser, Pierpaolo
Corrigan, Shannon
Hale, Matthew
Li, Chenhong
Veuille, Michel
Planes, Serge
Naylor, Gavin
Mona, Stefano
author_facet Maisano Delser, Pierpaolo
Corrigan, Shannon
Hale, Matthew
Li, Chenhong
Veuille, Michel
Planes, Serge
Naylor, Gavin
Mona, Stefano
author_sort Maisano Delser, Pierpaolo
collection PubMed
description Population genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene capture method to deep sequence ~1000 independent autosomal regions of a non-model organism, the blacktip reef shark (Carcharhinus melanopterus). We devised a sampling scheme based on the predictions of theoretical studies of metapopulations to show that sampling few individuals, but many loci, can be extremely informative to reconstruct the evolutionary history of species. We collected data from a single deme (SID) from Northern Australia and from a scattered sampling representing various locations throughout the Indian Ocean (SCD). We explored the genealogical signature of population dynamics detected from both sampling schemes using an ABC algorithm. We then contrasted these results with those obtained by fitting the data to a non-equilibrium finite island model. Both approaches supported an Nm value ~40, consistent with philopatry in this species. Finally, we demonstrate through simulation that metapopulations exhibit greater resilience to recent changes in effective size compared to unstructured populations. We propose an empirical approach to detect recent bottlenecks based on our sampling scheme.
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spelling pubmed-50306702016-09-26 Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives Maisano Delser, Pierpaolo Corrigan, Shannon Hale, Matthew Li, Chenhong Veuille, Michel Planes, Serge Naylor, Gavin Mona, Stefano Sci Rep Article Population genetics studies on non-model organisms typically involve sampling few markers from multiple individuals. Next-generation sequencing approaches open up the possibility of sampling many more markers from fewer individuals to address the same questions. Here, we applied a target gene capture method to deep sequence ~1000 independent autosomal regions of a non-model organism, the blacktip reef shark (Carcharhinus melanopterus). We devised a sampling scheme based on the predictions of theoretical studies of metapopulations to show that sampling few individuals, but many loci, can be extremely informative to reconstruct the evolutionary history of species. We collected data from a single deme (SID) from Northern Australia and from a scattered sampling representing various locations throughout the Indian Ocean (SCD). We explored the genealogical signature of population dynamics detected from both sampling schemes using an ABC algorithm. We then contrasted these results with those obtained by fitting the data to a non-equilibrium finite island model. Both approaches supported an Nm value ~40, consistent with philopatry in this species. Finally, we demonstrate through simulation that metapopulations exhibit greater resilience to recent changes in effective size compared to unstructured populations. We propose an empirical approach to detect recent bottlenecks based on our sampling scheme. Nature Publishing Group 2016-09-21 /pmc/articles/PMC5030670/ /pubmed/27651217 http://dx.doi.org/10.1038/srep33753 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Maisano Delser, Pierpaolo
Corrigan, Shannon
Hale, Matthew
Li, Chenhong
Veuille, Michel
Planes, Serge
Naylor, Gavin
Mona, Stefano
Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title_full Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title_fullStr Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title_full_unstemmed Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title_short Population genomics of C. melanopterus using target gene capture data: demographic inferences and conservation perspectives
title_sort population genomics of c. melanopterus using target gene capture data: demographic inferences and conservation perspectives
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5030670/
https://www.ncbi.nlm.nih.gov/pubmed/27651217
http://dx.doi.org/10.1038/srep33753
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