Assessing the population genetic structure and demographic history of Anopheles gambiae and Anopheles arabiensis at island and mainland sites in Uganda: implications for testing novel malaria vector control approaches

TL;DR

This study examines the genetic structure and population history of malaria-carrying mosquitoes in Uganda to inform new control strategies.

Contribution

The study provides new insights into the genetic differentiation and demographic history of Anopheles gambiae and Anopheles arabiensis in island and mainland Uganda.

Findings

Anopheles gambiae and Anopheles arabiensis show strong genetic differentiation between species but limited within-species variation.

Island populations of An. gambiae have lower diversity and smaller effective population sizes compared to mainland populations.

Anopheles arabiensis mainland populations show no significant genetic differentiation, suggesting panmixia.

Abstract

Despite substantial investments in malaria control, the disease remains a major burden in sub-Saharan Africa, particularly Uganda. Novel tools such as gene drive systems are being developed to suppress malaria vector populations, but their deployment requires detailed knowledge of mosquito population genetics.

The genetic structure, diversity, and demographic history of Anopheles gambiae and Anopheles arabiensis were assessed at six sites in Uganda: three islands in Lake Victoria and three mainland sites. A total of 2918 An, gambiae and 173 An. arabiensis were genotyped using targeted amplicon sequencing of 62 loci across coding and non-coding regions of the genome.

Population structure analyses revealed clear separation between the two species but little differentiation within each species across sites. Pairwise FST values among An. gambiae populations were low (0.00054–0.028) but often statistically significant, with mainland populations showing higher connectivity and island populations exhibiting greater isolation. Anopheles arabiensis mainland populations showed no statistically significant differentiation, suggesting panmixia. Principal component analysis and Bayesian clustering similarly distinguished species-level structure but no obvious substructure within sites.

Mainland An. gambiae populations displayed higher nucleotide diversity than island populations, while An. arabiensis showed the lowest diversity overall. Tajima’s D values were negative across sites, consistent with recent population expansions. Effective population size estimates indicated small populations at the islands (146–249) compared to large mainland populations (4054–8190).

These findings demonstrate strong genetic differentiation between An. gambiae and An. arabiensis, and subtle but meaningful structure between island and mainland An. gambiae populations. The reduced diversity and small effective population sizes at island sites suggest stronger genetic drift and limited gene flow, in contrast to the highly connected mainland populations.

This study highlights how geographic and ecological factors shape mosquito population structure and provides critical evidence for the design and monitoring of genetic-based vector control interventions, including the planning and evaluation of field trials.

The online version contains supplementary material available at 10.1186/s12936-025-05768-x.

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