Table1_Improved species assignments across the entire Anopheles genus using targeted sequencing.CSV

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.

准确鉴定按蚊属（Anopheles）蚊虫的物种，对于开展疟疾防控工作并评估防控成效至关重要。我们采用了此前开发的扩增子面板（ANOSPP），该面板可获取按蚊属任一物种的多个短核基因座的序列数据。物种鉴定基于采用k-mer（k聚体）距离将待测样本与参考索引进行比对。本研究提供了一套可对参考索引进行版本化管控更新的标准化流程，并展示其最新正式版本NNv2：相较于仅收录56个物种的前代版本NNv1，NNv2共涵盖91个物种。借助更新后的参考索引，我们能够对此前无法完成物种级鉴定的样本实现精准归类。我们还探讨了当待测物种未被参考索引收录时的处理方案，以及如何在未来的版本更新中优化该类问题的解决策略。为验证NNv2的性能提升效果，我们展示了对1789只采自马达加斯加的野外捕获蚊虫的物种鉴定结果，并证实可通过该扩增子测序数据检测到物种内部的种群结构。