# Microsatellite analysis of genetic differentiation among populations of the malaria vector Anopheles funestus across mainland Tanzania reveals contrasted patterns of geographic isolation and gene flow

## TL;DR

This study explores genetic differences in malaria-carrying mosquitoes across Tanzania, revealing patterns of isolation and gene flow.

## Contribution

The study provides new insights into the genetic structure of Anopheles funestus populations in Tanzania using microsatellite markers.

## Key findings

- Anopheles funestus populations in southeastern Tanzania show high genetic divergence from inland populations.
- Genetic divergence patterns suggest connectivity across the Rift Valley and distinctiveness of the Mtwara population.
- Anthropogenic gene flow may significantly influence population divergence despite geographical separation.

## Abstract

Despite Anopheles funestus s.s. being a highly competent and widespread malaria vector in Africa, its population structure remains largely understudied in many countries, including Tanzania. Herein, we examine the genetic diversity, geographic isolation, and gene flow of An. funestus populations across ten administrative regions in mainland Tanzania.

We employed 12 previously used microsatellite DNA markers to describe genetic diversity, isolation by distance, and gene flow patterns among ten An. funestus s.s. populations (n = 654) and one An. parensis population (n = 28), used as an outgroup, sampled across ten regions in mainland Tanzania.

Overall, allelic richness (Na) and genetic diversity (HS) did not differ significantly among populations. Although some loci and populations showed significant departures from Hardy–Weinberg equilibrium, the patterns were not indicative of substructuring within locations. Pairwise genetic divergence (FST) values indicated clear separation between An. parensis and An. funestus s.s., with values exceeding 0.2, consistent with species-level differentiation. Among An. funestus s.s. populations, the highest divergence was observed between southeastern coastal populations (Mtwara, Ruvuma, Lindi) and inland populations, with FST values up to 0.288. There was no evidence of isolation by distance. Instead, patterns of genetic divergence suggested connectivity across the Rift Valley and heterogeneity among southeastern populations. Neighbor-joining analysis and Bayesian genotype clustering identified three distinct population groups: (i) An. parensis (Dodoma), (ii) a genetically distinct An. funestus s.s. population from Mtwara, and (iii) a more homogeneous cluster comprising the remaining An. funestus s.s. populations. Notably, the Mtwara population appeared highly differentiated, with divergence approaching that between An. funestus s.s. and An. parensis, supporting its distinctiveness but not undermining the role of An. parensis as an outgroup.

Except for the Mtwara population, whose status will need to be clarified through whole-genome sequencing, moderate genetic divergence was found among An. funestus s.s. populations across Tanzania, despite geographical separation and the Rift Valley. The observed genetic structure suggests that anthropogenic gene flow may play a key role in shaping population divergence. Future studies should aim to delineate the effects of local adaptation from recent gene flow to further explore these dynamics

The online version contains supplementary material available at 10.1186/s13071-025-07080-8.