Genomic signatures of selection in <i>Anopheles funestus</i> reveal shared and population-specific adaptive variation across African populations

Abstract

Abstract Insecticide resistance in Anopheles funestus threatens malaria vector control across sub-Saharan Africa, yet genomic signatures of selection across geographically structured populations remain poorly understood. We analysed whole-genome sequence data from 635 An. funestus mosquitoes from West (Senegal, Guinea, Nigeria), Central (Cameroon), and East Africa (Kenya) to characterise population structure and identify targets of recent positive selection. Population genomic analyses revealed strong differentiation between East African and West/Central African populations, with finer-scale structuring within West Africa. Genome-wide selection scans using H12 identified sweep regions on chromosome arms 2RL and 3RL, overlapping a cytochrome P450 cluster and the gamma-aminobutyric acid (GABA) receptor locus respectively. iSAFE prioritised candidate variants within these sweeps: non-synonymous substitutions in CYP6A14 were identified at high frequencies in Guinea, Nigeria, and Cameroon, while population-restricted variants implicated octopamine receptor genes on 2RL and the GABA receptor on 3RL. Diplotype clustering and copy number variation analyses confirmed the causal role of candidate variants, embedded within extended haplotypes of reduced heterozygosity consistent with recent positive selection. These findings demonstrate that adaptive evolution in An. funestus reflects both shared and population-specific selective processes shaped by geography and ecological context. Whereas selection on detoxification pathways appears widespread, localised signals in neuromodulatory loci, including the GABA receptor and octopamine-related genes, reveal that biological systems beyond metabolic resistance contribute to mosquito adaptation. The convergence of selective signals across these gene classes highlights neuromodulatory pathways as potential complementary targets for next-generation vector control strategies.