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Mosquitoes have profoundly affected human history and continue to threaten human health through the transmission of a diverse array of pathogens. The phylogeny of mosquitoes has remained poorly characterized due to difficulty in taxonomic sampling and limited availability of genomic data beyond the most important vector species. Here, we used phylogenomic analysis of 709 single copy ortholog groups from 256 mosquito species to produce a strongly supported phylogeny that resolves the position of the major disease vector species and the major mosquito lineages. Our analyses support an origin of mosquitoes in the early Triassic (217 MYA [highest posterior density region: 188–250 MYA]), considerably older than previous estimates. Moreover, we utilize an extensive database of host associations for mosquitoes to show that mosquitoes have shifted to feeding upon the blood of mammals numerous times, and that mosquito diversification and host-use patterns within major lineages appear to coincide in earth history both with major continental drift events and with the diversification of vertebrate classes.

 

Abstract With over 3500 mosquito species described, accurate species identification of the few implicated in disease transmission is critical to mosquito borne disease mitigation. Yet this task is hindered by limited global taxonomic expertise and specimen damage consistent across common capture methods. Convolutional neural networks (CNNs) are promising with limited sets of species, but image database requirements restrict practical implementation. Using an image database of 2696 specimens from 67 mosquito species, we address the practical open-set problem with a detection algorithm for novel species. Closed-set classification of 16 known species achieved 97.04 ± 0.87% accuracy independently, and 89.07 ± 5.58% when cascaded with novelty detection. Closed-set classification of 39 species produces a macro F1-score of 86.07 ± 1.81%. This demonstrates an accurate, scalable, and practical computer vision solution to identify wild-caught mosquitoes for implementation in biosurveillance and targeted vector control programs, without the need for extensive image database development for each new target region. 

Scientific collections such as the U.S. National Museum (USNM) are critical to filling knowledge gaps in molecular systematics studies. The global taxonomic impediment has resulted in a reduction of expert taxonomists generating new collections of rare or understudied taxa and these large historic collections may be the only reliable source of material for some taxa. Integrated systematics studies using both morphological examinations and DNA sequencing are often required for resolving many taxonomic issues but as DNA methods often require partial or complete destruction of a sample, there are many factors to consider before implementing destructive sampling of specimens within scientific collections. We present a methodology for the use of archive specimens that includes two crucial phases: 1) thoroughly documenting specimens destined for destructive sampling—a process called electronic vouchering, and 2) the pipeline used for whole genome sequencing of archived specimens, from extraction of genomic DNA to assembly of putative genomes with basic annotation. The process is presented for eleven specimens from two different insect subfamilies of medical importance to humans: Anophelinae (Diptera: Culicidae)—mosquitoes and Triatominae (Hemiptera: Reduviidae)—kissing bugs. Assembly of whole mitochondrial genome sequences of all 11 specimens along with the results of an ortholog search and BLAST against the NCBI nucleotide database are also presented.