Assessing connectivity despite high diversity in island populations of a malaria mosquito
Abstract 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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-02-01
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| Series: | Evolutionary Applications |
| Subjects: | |
| Online Access: | https://doi.org/10.1111/eva.12878 |
| _version_ | 1818342467406135296 |
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| author | Christina M. Bergey Martin Lukindu Rachel M. Wiltshire Michael C. Fontaine Jonathan K. Kayondo Nora J. Besansky |
| author_facet | Christina M. Bergey Martin Lukindu Rachel M. Wiltshire Michael C. Fontaine Jonathan K. Kayondo Nora J. Besansky |
| author_sort | Christina M. Bergey |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-12-13T16:15:09Z |
| format | Article |
| id | doaj.art-768722f1a83e46a483880bdc2c8af1f5 |
| institution | Directory Open Access Journal |
| issn | 1752-4571 |
| language | English |
| last_indexed | 2024-12-13T16:15:09Z |
| publishDate | 2020-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Evolutionary Applications |
| spelling | doaj.art-768722f1a83e46a483880bdc2c8af1f52022-12-21T23:38:51ZengWileyEvolutionary Applications1752-45712020-02-0113241743110.1111/eva.12878Assessing connectivity despite high diversity in island populations of a malaria mosquitoChristina M. Bergey0Martin Lukindu1Rachel M. Wiltshire2Michael C. Fontaine3Jonathan K. Kayondo4Nora J. Besansky5Department of Biological Sciences University of Notre Dame Notre Dame IN USADepartment of Biological Sciences University of Notre Dame Notre Dame IN USADepartment of Biological Sciences University of Notre Dame Notre Dame IN USAGroningen Institute for Evolutionary Life Sciences (GELIFES) University of Groningen Groningen The NetherlandsDepartment of Entomology Uganda Virus Research Institute (UVRI) Entebbe UgandaDepartment of Biological Sciences University of Notre Dame Notre Dame IN USAAbstract 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.https://doi.org/10.1111/eva.12878Anopheles gambiaegene drive technologygene flowmalariamigration |
| spellingShingle | Christina M. Bergey Martin Lukindu Rachel M. Wiltshire Michael C. Fontaine Jonathan K. Kayondo Nora J. Besansky Assessing connectivity despite high diversity in island populations of a malaria mosquito Evolutionary Applications Anopheles gambiae gene drive technology gene flow malaria migration |
| 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 | Anopheles gambiae gene drive technology gene flow malaria migration |
| url | https://doi.org/10.1111/eva.12878 |
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