Combining genetic crosses and pool targeted DNA‐seq for untangling genomic variations associated with resistance to multiple insecticides in the mosquito Aedes aegypti

In addition to combating vector‐borne diseases, studying the adaptation of mosquitoes to insecticides provides a remarkable example of evolution‐in‐action driving the selection of complex phenotypes. Actually, most resistant mosquito populations show multi‐resistance phenotypes as a consequence of the variety of insecticides employed and of the complexity of selected resistance mechanisms. Such complexity makes the identification of alleles conferring resistance to specific insecticides challenging and prevents the development of molecular assays to track them in the field. Here we showed that combining simple genetic crosses with pool targeted DNA‐seq can enhance the specificity of resistance allele's detection while maintaining experimental work and sequencing effort at reasonable levels. A multi‐resistant population of the mosquito Aedes aegypti was exposed to three distinct insecticides (deltamethrin, bendiocarb and fenitrothion), and survivors to each insecticide were crossed with a susceptible strain to generate three distinct lines. F2 individuals from each line were then segregated based on their survival to two insecticide doses. Hundreds of genes covering all detoxifying enzymes and insecticide targets together with more than 7,000 intergenic regions equally spread over mosquito genome were sequenced from pools of F0 and F2 individuals unexposed or surviving insecticide. Differential coverage analysis identified 39 detoxification enzymes showing an increased gene copy number in association with resistance. Combining an allele frequency filtering approach with a Bayesian F (ST)‐based genome scan identified multiple genomic regions showing strong selection signatures together with 50 nonsynonymous variations associated with resistance. This study provides a simple and cost‐effective approach to improve the specificity of resistance allele's detection in multi‐resistant populations while reducing false positives frequently arising when comparing populations showing divergent genetic backgrounds. The identification of novel DNA resistance markers opens new opportunities for improving the tracking of insecticide resistance in the field.