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The primary control methods for the African malaria mosquito, Anopheles gambiae , are based on insecticidal interventions. Emerging resistance to these compounds is therefore of major concern to malaria control programmes. The organophosphate, pirimiphos-methyl, is a relatively new chemical in the vector control armoury but is now widely used in indoor residual spray campaigns. Whilst generally effective, phenotypic resistance has developed in some areas in malaria vectors. Here, we used a population genomic approach to identify novel mechanisms of resistance to pirimiphos-methyl in Anopheles gambiae s.l mosquitoes. In multiple populations, we found large and repeated signals of selection at a locus containing a cluster of detoxification enzymes, some of whose orthologs are known to confer resistance to organophosphates in Culex pipiens . Close examination revealed a pair of alpha-esterases, Coeae1f and Coeae2f , and a complex and diverse pattern of haplotypes under selection in An. gambiae, An. coluzzii and An. arabiensis . As in Cx. pipiens , copy number variation seems to play a role in the evolution of insecticide resistance at this locus. We used diplotype clustering to examine whether these signals arise from parallel evolution or adaptive introgression. Using whole-genome sequenced phenotyped samples, we found that in West Africa, a copy number variant in Anopheles gambiae is associated with resistance to pirimiphos-methyl. Overall, we demonstrate a striking example of contemporary parallel evolution which has important implications for malaria control programmes.

Background: The Global Program to Eliminate Lymphatic Filariasis is the largest public health program based on mass drug administration (MDA). Despite decades of MDA, ongoing transmission in some countries remains a challenge. To optimize interventions, it is essential to differentiate between recrudescence (poor drug response and persistent infection) and new infections (ongoing transmission). Since adult filariae are inaccessible in humans, an approach that relies on genotyping the offspring microfilariae (mf) is required., Methods: We utilized Brugia malayi adults and mf obtained from gerbils with a known pedigree to develop and validate our whole-genome amplification and kinship analysis approach. We then sequenced the genomes of Wuchereria bancrofti mf from infected humans from Côte d'Ivoire (CDI), characterized the population genetic diversity, and made inferences about the adult breeders. We developed a whole-exome capture panel for W. bancrofti to enrich parasite nuclear DNA from lower-quality samples contaminated with host DNA., Results: We established a robust analysis pipeline using B. malayi adult and mf. We estimated the pre-treatment genetic diversity in W. bancrofti from 269 mf collected from 18 individuals, and further analyzed 1-year post-treatment samples of 74 mf from 4 individuals. By reconstructing and temporally tracking sibling relationships across pre- and post-treatment samples, we differentiated between new and established maternal families, suggesting reinfection in one subject and recrudescence in three subjects. Estimated reproductively active adult females ranged between 3 and 9 in the studied subjects. Hemizygosity of the male X-chromosome allowed for direct inference of haplotypes, facilitating robust maternal parentage inference, even when the genetic diversity was low. Population structure analysis revealed genetically distinct parasites among our CDI samples. Sequence composition and variant analysis of whole-exome libraries showed that the hybridization capture approach can effectively enrich parasite nuclear DNA and identify protein-coding variants with ∼95% genotype concordance rate., Conclusions: We have generated resources to facilitate development of field-deployable genotyping tools that can estimate worm burdens and monitor parasite populations. These tools are essential for the success of lymphatic filariasis MDA programs. With further expansion of the databases to include geographically diverse samples, we will be able to spatially track parasite movement associated with host/vector migration.

Resistance to insecticides in Anopheles mosquitoes threatens the effectiveness of the most widespread tools currently used to control malaria. The genetic underpinnings of resistance are still only partially understood, with much of the variance in resistance phenotype left unexplained. We performed a multi-country large scale genome-wide association study of resistance to two insecticides widely used in malaria control: deltamethrin and pirimiphos-methyl. Using a bioassay methodology designed to maximise the phenotypic difference between resistant and susceptible samples, we sequenced 969 phenotyped female An. gambiae and An. coluzzii from ten locations across four countries in West Africa (Benin, Côte d'Ivoire, Ghana and Togo), identifying single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) segregating in the populations. The patterns of resistance association were highly multiallelic and variable between populations, with different genomic regions contributing to resistance, as well as different mutations within a given region. While the strongest and most consistent association with deltamethrin resistance came from the region around Cyp6aa1 , this resistance was based on a combination of several independent CNVs in An. coluzzii , and on a non-CNV bearing haplotype in An. gambiae . Further signals involved a range of cytochrome P450, mitochondrial, and immunity genes. Similarly, for pirimiphos-methyl, while the strongest signal came from the region of Ace1 , more widespread signals included cytochrome P450s, glutathione S-transferases, and a subunit of the nAChR target site of neonicotinoid insecticides. The regions around Cyp9k1 and the Tep family of immune genes were associated with resistance to both insecticide classes, suggesting possible cross-resistance mechanisms. These locally-varying, multigenic and multiallelic patterns highlight the challenges involved in genomic monitoring and surveillance of resistance, and form the basis for improvement of methods used to detect and predict resistance. Based on simulations of resistance variants, we recommend that yet larger scale studies, exceeding 500 phenotyped samples per population, are required to better identify associated genomic regions.