Improved species assignments across the entire Anopheles genus using targeted sequencing

Abstract

Accurate species identification of the mosquitoes in the genus Anopheles is of crucial importance to implement malaria control measures and monitor their effectiveness. We use a previously developed amplicon panel (ANOSPP) that retrieves sequence data from multiple short nuclear loci for any species in the genus. Species assignment is based on comparison of samples to a reference index using k-mer distance. Here, we provide a protocol to generate version controlled updates of the reference index and present its latest release, NNv2, which contains 91 species, compared to 56 species represented in its predecessor NNv1. With the updated reference index, we are able to assign samples to species level that previously could not be assigned. We discuss what happens if a species is not represented in the reference index and how this can be addressed in a future update. To demonstrate the increased power of NNv2, we showcase the assignments of 1789 wild-caught mosquitoes from Madagascar and demonstrate that we can detect within species population structure from the amplicon sequencing data.