Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutral variation with assays of the structure of selected variation, demonstrated using populations of the principal African malaria vector Anopheles gambiae. Accurate estimation of mosquito migration is crucial for efforts to combat malaria. Modeling and cage experiments suggest that mosquito gene drive systems will enable malaria eradication, but establishing safety and efficacy requires identification of isolated populations in which to conduct field testing. We assess Lake Victoria islands as candidate sites, finding one island 30 km offshore is as differentiated from mainland samples as populations from across the continent. Collectively, our results suggest sufficient contemporary isolation of these islands to warrant consideration as field‐testing locations and illustrate shared adaptive variation as a useful proxy for connectivity in highly polymorphic species.

BackgroundUnderstanding population genetic structure in the malaria vector Anopheles gambiae (s.s.) is crucial to inform genetic control and manage insecticide resistance. Unfortunately, species characteristics such as high nucleotide diversity, large effective population size, recent range expansion, and high dispersal ability complicate the inference of genetic structure across its range in sub-Saharan Africa. The ocean, along with the Great Rift Valley, is one of the few recognized barriers to gene flow in this species, but the effect of inland lakes, which could be useful sites for initial testing of genetic control strategies, is relatively understudied. Here we examine Lake Victoria as a barrier between the Ugandan mainland and the Ssese Islands, which lie up to 60 km offshore. We use mitochondrial DNA (mtDNA) from populations sampled in 2002, 2012 and 2015, and perform Bayesian cluster analysis on mtDNA combined with microsatellite data previously generated from the same 2002 mosquito DNA samples.ResultsHierarchical analysis of molecular variance and Bayesian clustering support significant differentiation between the mainland and lacustrine islands. In an mtDNA haplotype network constructed from this and previous data, haplotypes are shared even between localities separated by the Rift Valley, a result that more likely reflects retention of shared ancestral polymorphism than contemporary gene flow.ConclusionsThe relative genetic isolation of An. gambiae on the Ssese Islands, their small size, level terrain and ease of access from the mainland, the relative simplicity of the vectorial system, and the prevalence of malaria, are all attributes that recommend these islands as possible sites for the testing of genetic control strategies.

Polymorphic chromosomal inversions have been implicated in local adaptation. In anopheline mosquitoes, inversions also contribute to epidemiologically relevant phenotypes such as resting behavior. Progress in understanding these phenotypes and their mechanistic basis has been hindered because the only available method for inversion genotyping relies on traditional cytogenetic karyotyping, a rate-limiting and technically difficult approach that is possible only for the fraction of the adult female population at the correct gonotrophic stage. Here, we focus on an understudied malaria vector of major importance in sub-Saharan Africa, Anopheles funestus. We ascertain and validate tag single nucleotide polymorphisms (SNPs) using high throughput molecular assays that allow rapid inversion genotyping of the three most common An. funestus inversions at scale, overcoming the cytogenetic karyotyping barrier. These same inversions are the only available markers for distinguishing two An. funestus ecotypes that differ in indoor resting behavior, Folonzo and Kiribina. Our new inversion genotyping tools will facilitate studies of ecotypic differentiation in An. funestus and provide a means to improve our understanding of the roles of Folonzo and Kiribina in malaria transmission.

Documenting isolation is notoriously difficult for species with vast polymorphic populations. High proportions of shared variation impede estimation of connectivity, even despite leveraging information from many genetic markers. We overcome these impediments by combining classical analysis of neutral variation with assays of the structure of selected variation, demonstrated using populations of the principal African malaria vector Anopheles gambiae. Accurate estimation of mosquito migration is crucial for efforts to combat malaria. Modeling and cage experiments suggest that mosquito gene drive systems will enable malaria eradication, but establishing safety and efficacy requires identification of isolated populations in which to conduct field-testing. We assess Lake Victoria islands as candidate sites, finding one island 30 kilometers offshore is as differentiated from mainland samples as populations from across the continent. Collectively, our results suggest sufficient contemporary isolation of these islands to warrant consideration as field-testing locations and illustrate shared adaptive variation as a useful proxy for connectivity in highly polymorphic species.