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Assessing connectivity despite high diversity in island populations of a malaria mosquito

Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutra...

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Detalles Bibliográficos
Autores principales: Bergey, Christina M., Lukindu, Martin, Wiltshire, Rachel M., Fontaine, Michael C., Kayondo, Jonathan K., Besansky, Nora J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976967/
https://www.ncbi.nlm.nih.gov/pubmed/31993086
http://dx.doi.org/10.1111/eva.12878
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author Bergey, Christina M.
Lukindu, Martin
Wiltshire, Rachel M.
Fontaine, Michael C.
Kayondo, Jonathan K.
Besansky, Nora J.
author_facet Bergey, Christina M.
Lukindu, Martin
Wiltshire, Rachel M.
Fontaine, Michael C.
Kayondo, Jonathan K.
Besansky, Nora J.
author_sort Bergey, Christina M.
collection PubMed
description Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutral variation with assays of the structure of selected variation, demonstrated using populations of the principal African malaria vector Anopheles gambiae. Accurate estimation of mosquito migration is crucial for efforts to combat malaria. Modeling and cage experiments suggest that mosquito gene drive systems will enable malaria eradication, but establishing safety and efficacy requires identification of isolated populations in which to conduct field testing. We assess Lake Victoria islands as candidate sites, finding one island 30 km offshore is as differentiated from mainland samples as populations from across the continent. Collectively, our results suggest sufficient contemporary isolation of these islands to warrant consideration as field‐testing locations and illustrate shared adaptive variation as a useful proxy for connectivity in highly polymorphic species.
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spelling pubmed-69769672020-01-28 Assessing connectivity despite high diversity in island populations of a malaria mosquito Bergey, Christina M. Lukindu, Martin Wiltshire, Rachel M. Fontaine, Michael C. Kayondo, Jonathan K. Besansky, Nora J. Evol Appl Original Articles Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutral variation with assays of the structure of selected variation, demonstrated using populations of the principal African malaria vector Anopheles gambiae. Accurate estimation of mosquito migration is crucial for efforts to combat malaria. Modeling and cage experiments suggest that mosquito gene drive systems will enable malaria eradication, but establishing safety and efficacy requires identification of isolated populations in which to conduct field testing. We assess Lake Victoria islands as candidate sites, finding one island 30 km offshore is as differentiated from mainland samples as populations from across the continent. Collectively, our results suggest sufficient contemporary isolation of these islands to warrant consideration as field‐testing locations and illustrate shared adaptive variation as a useful proxy for connectivity in highly polymorphic species. John Wiley and Sons Inc. 2019-10-28 /pmc/articles/PMC6976967/ /pubmed/31993086 http://dx.doi.org/10.1111/eva.12878 Text en © 2019 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Bergey, Christina M.
Lukindu, Martin
Wiltshire, Rachel M.
Fontaine, Michael C.
Kayondo, Jonathan K.
Besansky, Nora J.
Assessing connectivity despite high diversity in island populations of a malaria mosquito
title Assessing connectivity despite high diversity in island populations of a malaria mosquito
title_full Assessing connectivity despite high diversity in island populations of a malaria mosquito
title_fullStr Assessing connectivity despite high diversity in island populations of a malaria mosquito
title_full_unstemmed Assessing connectivity despite high diversity in island populations of a malaria mosquito
title_short Assessing connectivity despite high diversity in island populations of a malaria mosquito
title_sort assessing connectivity despite high diversity in island populations of a malaria mosquito
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6976967/
https://www.ncbi.nlm.nih.gov/pubmed/31993086
http://dx.doi.org/10.1111/eva.12878
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