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Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America

BACKGROUND: Anopheles darlingi is the most important malaria vector in the Neotropics. An understanding of A. darlingi's population structure and contemporary gene flow patterns is necessary if vector populations are to be successfully controlled. We assessed population genetic structure and le...

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Autores principales: Mirabello, Lisa, Vineis, Joseph H, Yanoviak, Stephen P, Scarpassa, Vera M, Póvoa, Marinete M, Padilla, Norma, Achee, Nicole L, Conn, Jan E
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2292152/
https://www.ncbi.nlm.nih.gov/pubmed/18366795
http://dx.doi.org/10.1186/1472-6785-8-3
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author Mirabello, Lisa
Vineis, Joseph H
Yanoviak, Stephen P
Scarpassa, Vera M
Póvoa, Marinete M
Padilla, Norma
Achee, Nicole L
Conn, Jan E
author_facet Mirabello, Lisa
Vineis, Joseph H
Yanoviak, Stephen P
Scarpassa, Vera M
Póvoa, Marinete M
Padilla, Norma
Achee, Nicole L
Conn, Jan E
author_sort Mirabello, Lisa
collection PubMed
description BACKGROUND: Anopheles darlingi is the most important malaria vector in the Neotropics. An understanding of A. darlingi's population structure and contemporary gene flow patterns is necessary if vector populations are to be successfully controlled. We assessed population genetic structure and levels of differentiation based on 1,376 samples from 31 localities throughout the Peruvian and Brazilian Amazon and Central America using 5–8 microsatellite loci. RESULTS: We found high levels of polymorphism for all of the Amazonian populations (mean R(S )= 7.62, mean H(O )= 0.742), and low levels for the Belize and Guatemalan populations (mean R(S )= 4.3, mean H(O )= 0.457). The Bayesian clustering analysis revealed five population clusters: northeastern Amazonian Brazil, southeastern and central Amazonian Brazil, western and central Amazonian Brazil, Peruvian Amazon, and the Central American populations. Within Central America there was low non-significant differentiation, except for between the populations separated by the Maya Mountains. Within Amazonia there was a moderate level of significant differentiation attributed to isolation by distance. Within Peru there was no significant population structure and low differentiation, and some evidence of a population expansion. The pairwise estimates of genetic differentiation between Central America and Amazonian populations were all very high and highly significant (F(ST )= 0.1859 – 0.3901, P < 0.05). Both the D(A )and F(ST )distance-based trees illustrated the main division to be between Central America and Amazonia. CONCLUSION: We detected a large amount of population structure in Amazonia, with three population clusters within Brazil and one including the Peru populations. The considerable differences in N(e )among the populations may have contributed to the observed genetic differentiation. All of the data suggest that the primary division within A. darlingi corresponds to two white gene genotypes between Amazonia (genotype 1) and Central America, parts of Colombia and Venezuela (genotype 2), and are in agreement with previously published mitochondrial COI gene sequences interpreted as incipient species. Overall, it appears that two main factors have contributed to the genetic differentiation between the population clusters: physical distance between the populations and the differences in effective population sizes among the subpopulations.
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spelling pubmed-22921522008-04-11 Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America Mirabello, Lisa Vineis, Joseph H Yanoviak, Stephen P Scarpassa, Vera M Póvoa, Marinete M Padilla, Norma Achee, Nicole L Conn, Jan E BMC Ecol Research Article BACKGROUND: Anopheles darlingi is the most important malaria vector in the Neotropics. An understanding of A. darlingi's population structure and contemporary gene flow patterns is necessary if vector populations are to be successfully controlled. We assessed population genetic structure and levels of differentiation based on 1,376 samples from 31 localities throughout the Peruvian and Brazilian Amazon and Central America using 5–8 microsatellite loci. RESULTS: We found high levels of polymorphism for all of the Amazonian populations (mean R(S )= 7.62, mean H(O )= 0.742), and low levels for the Belize and Guatemalan populations (mean R(S )= 4.3, mean H(O )= 0.457). The Bayesian clustering analysis revealed five population clusters: northeastern Amazonian Brazil, southeastern and central Amazonian Brazil, western and central Amazonian Brazil, Peruvian Amazon, and the Central American populations. Within Central America there was low non-significant differentiation, except for between the populations separated by the Maya Mountains. Within Amazonia there was a moderate level of significant differentiation attributed to isolation by distance. Within Peru there was no significant population structure and low differentiation, and some evidence of a population expansion. The pairwise estimates of genetic differentiation between Central America and Amazonian populations were all very high and highly significant (F(ST )= 0.1859 – 0.3901, P < 0.05). Both the D(A )and F(ST )distance-based trees illustrated the main division to be between Central America and Amazonia. CONCLUSION: We detected a large amount of population structure in Amazonia, with three population clusters within Brazil and one including the Peru populations. The considerable differences in N(e )among the populations may have contributed to the observed genetic differentiation. All of the data suggest that the primary division within A. darlingi corresponds to two white gene genotypes between Amazonia (genotype 1) and Central America, parts of Colombia and Venezuela (genotype 2), and are in agreement with previously published mitochondrial COI gene sequences interpreted as incipient species. Overall, it appears that two main factors have contributed to the genetic differentiation between the population clusters: physical distance between the populations and the differences in effective population sizes among the subpopulations. BioMed Central 2008-03-26 /pmc/articles/PMC2292152/ /pubmed/18366795 http://dx.doi.org/10.1186/1472-6785-8-3 Text en Copyright © 2008 Mirabello et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Mirabello, Lisa
Vineis, Joseph H
Yanoviak, Stephen P
Scarpassa, Vera M
Póvoa, Marinete M
Padilla, Norma
Achee, Nicole L
Conn, Jan E
Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title_full Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title_fullStr Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title_full_unstemmed Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title_short Microsatellite data suggest significant population structure and differentiation within the malaria vector Anopheles darlingi in Central and South America
title_sort microsatellite data suggest significant population structure and differentiation within the malaria vector anopheles darlingi in central and south america
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2292152/
https://www.ncbi.nlm.nih.gov/pubmed/18366795
http://dx.doi.org/10.1186/1472-6785-8-3
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