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Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study

This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we p...

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Autores principales: Hubbard, Alfred, Hemming-Schroeder, Elizabeth, Machani, Maxwell Gesuge, Afrane, Yaw, Yan, Guiyun, Lo, Eugenia, Janies, Daniel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694861/
https://www.ncbi.nlm.nih.gov/pubmed/36645165
http://dx.doi.org/10.1111/mec.16846
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author Hubbard, Alfred
Hemming-Schroeder, Elizabeth
Machani, Maxwell Gesuge
Afrane, Yaw
Yan, Guiyun
Lo, Eugenia
Janies, Daniel
author_facet Hubbard, Alfred
Hemming-Schroeder, Elizabeth
Machani, Maxwell Gesuge
Afrane, Yaw
Yan, Guiyun
Lo, Eugenia
Janies, Daniel
author_sort Hubbard, Alfred
collection PubMed
description This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics.
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spelling pubmed-106948612023-12-04 Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study Hubbard, Alfred Hemming-Schroeder, Elizabeth Machani, Maxwell Gesuge Afrane, Yaw Yan, Guiyun Lo, Eugenia Janies, Daniel Mol Ecol Article This study employs landscape genetics to investigate the environmental drivers of a deadly vector-borne disease, malaria caused by Plasmodium falciparum, in a more spatially comprehensive manner than any previous work. With 1804 samples from 44 sites collected in western Kenya in 2012 and 2013, we performed resistance surface analysis to show that Lake Victoria acts as a barrier to transmission between areas north and south of the Winam Gulf. In addition, Mantel correlograms clearly showed significant correlations between genetic and geographic distance over short distances (less than 70 km). In both cases, we used an identity-by-state measure of relatedness tailored to find highly related individual parasites in order to focus on recent gene flow that is more relevant to disease transmission. To supplement these results, we performed conventional population genetics analyses, including Bayesian clustering methods and spatial ordination techniques. These analyses revealed some differentiation on the basis of geography and elevation and a cluster of genetic similarity in the lowlands north of the Winam Gulf of Lake Victoria. Taken as a whole, these results indicate low overall genetic differentiation in the Lake Victoria region, but with some separation of parasite populations north and south of the Winam Gulf that is explained by the presence of the lake as a geographic barrier to gene flow. We recommend similar landscape genetics analyses in future molecular epidemiology studies of vector-borne diseases to extend and contextualize the results of traditional population genetics. 2023-04 2023-02-01 /pmc/articles/PMC10694861/ /pubmed/36645165 http://dx.doi.org/10.1111/mec.16846 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Article
Hubbard, Alfred
Hemming-Schroeder, Elizabeth
Machani, Maxwell Gesuge
Afrane, Yaw
Yan, Guiyun
Lo, Eugenia
Janies, Daniel
Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title_full Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title_fullStr Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title_full_unstemmed Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title_short Implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: A malaria case study
title_sort implementing landscape genetics in molecular epidemiology to determine drivers of vector-borne disease: a malaria case study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694861/
https://www.ncbi.nlm.nih.gov/pubmed/36645165
http://dx.doi.org/10.1111/mec.16846
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