Partial connectivity and fine-scale population structure in Honduran Anopheles albimanus inferred from microsatellite markers

<title>Abstract</title> Background Understanding population connectivity in malaria vectors is important for surveillance in elimination settings, where local dispersal and population subdivision may influence residual transmission and the spread of adaptive traits. <italic>Anopheles albimanus</italic> is the major malaria vector in Honduras, yet its population structure remains poorly characterized. This study aimed to assess the genetic diversity and population structure of Honduran <italic>An. albimanus</italic> populations using microsatellite markers. Methods Adult mosquitoes collected from ten populations across Honduras (n = 176) were genotyped at eight species-specific microsatellite loci. Genetic diversity was estimated using number of alleles, effective number of alleles, observed and expected heterozygosity, and Wright’s fixation index. Population differentiation was evaluated using pairwise FST estimates and analysis of molecular variance (AMOVA). A hierarchical AMOVA was used to assess regional structure, and Bayesian clustering implemented in STRUCTURE was used to infer genetic clusters, with the most likely number of clusters determined using the Evanno ΔK method. Results All loci were polymorphic and showed moderate to high genetic diversity (He = 0.513–0.817). Observed heterozygosity was consistently lower than expected, with widespread heterozygote deficits and frequent departures from Hardy–Weinberg equilibrium across populations. Pairwise FST values ranged from 0.008 to 0.195, indicating heterogeneous levels of genetic connectivity. AMOVA showed that 88% of genetic variation occurred within populations and 12% among populations (PhiPT = 0.117, p &lt; 0.001), consistent with moderate but significant differentiation. Hierarchical AMOVA indicated minimal differentiation between La Mosquitia and the rest of Honduras (PhiRT = 0.012), while Bayesian clustering supported two inferred genetic clusters (K = 2) with evidence of admixture across populations, and Mantel analysis detected no evidence of isolation by distance. Conclusions Honduran <italic>An. albimanus</italic> populations harbour substantial genetic diversity while exhibiting moderate differentiation and fine-scale substructure despite overall connectivity. These findings support a model of partial connectivity shaped primarily by local population-level processes and highlight the utility of microsatellite markers for detecting contemporary population structure relevant to malaria vector surveillance and control in elimination settings.

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Journal
Parasites & Vectors
Published
2026-08-18
DOI
https://doi.org/10.1186/s13071-026-07626-4
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00

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article

Partial connectivity and fine-scale population structure in Honduran Anopheles albimanus inferred from microsatellite markers

Alejandra Pinto, Denis Escobar, Aida Mejia, Gustavo Fontecha
Parasites & Vectors
Malaria Research and Control
article

Partial connectivity and fine-scale population structure in Honduran Anopheles albimanus inferred from microsatellite markers

Alejandra Pinto, Denis Escobar, Aida Mejia, Gustavo Fontecha
article en

Abstract

<title>Abstract</title> Background Understanding population connectivity in malaria vectors is important for surveillance in elimination settings, where local dispersal and population subdivision may influence residual transmission and the spread of adaptive traits. <italic>Anopheles albimanus</italic> is the major malaria vector in Honduras, yet its population structure remains poorly characterized. This study aimed to assess the genetic diversity and population structure of Honduran <italic>An. albimanus</italic> populations using microsatellite markers. Methods Adult mosquitoes collected from ten populations across Honduras (n = 176) were genotyped at eight species-specific microsatellite loci. Genetic diversity was estimated using number of alleles, effective number of alleles, observed and expected heterozygosity, and Wright’s fixation index. Population differentiation was evaluated using pairwise FST estimates and analysis of molecular variance (AMOVA). A hierarchical AMOVA was used to assess regional structure, and Bayesian clustering implemented in STRUCTURE was used to infer genetic clusters, with the most likely number of clusters determined using the Evanno ΔK method. Results All loci were polymorphic and showed moderate to high genetic diversity (He = 0.513–0.817). Observed heterozygosity was consistently lower than expected, with widespread heterozygote deficits and frequent departures from Hardy–Weinberg equilibrium across populations. Pairwise FST values ranged from 0.008 to 0.195, indicating heterogeneous levels of genetic connectivity. AMOVA showed that 88% of genetic variation occurred within populations and 12% among populations (PhiPT = 0.117, p &lt; 0.001), consistent with moderate but significant differentiation. Hierarchical AMOVA indicated minimal differentiation between La Mosquitia and the rest of Honduras (PhiRT = 0.012), while Bayesian clustering supported two inferred genetic clusters (K = 2) with evidence of admixture across populations, and Mantel analysis detected no evidence of isolation by distance. Conclusions Honduran <italic>An. albimanus</italic> populations harbour substantial genetic diversity while exhibiting moderate differentiation and fine-scale substructure despite overall connectivity. These findings support a model of partial connectivity shaped primarily by local population-level processes and highlight the utility of microsatellite markers for detecting contemporary population structure relevant to malaria vector surveillance and control in elimination settings.

Parasites & Vectors
National Autonomous University of Honduras (HN)
Universidad Nacional Autonoma de Honduras
Openalex Percentile: Top 45%
Malaria Research and Control
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