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Published on: September 10, 2021
Identification of Swedish mosquitoes based on molecular barcoding of the COI gene and SNP analysis
Cecilia Engdahl1, Pär Larsson, Jonas Näslund
1Swedish Defense Research Agency, CBRN Defense and Security, Umeå, SE-901 82, Sweden; Department of Clinical Microbiology, Virology, Umeå University, Umeå, SE-901 85, Sweden; Department of Clinical Microbiology, Infectious Diseases, Umeå University, Umeå, SE-901 85, Sweden.
Abstract:
Mosquito-borne infectious diseases are emerging in many regions of the world. Consequently, surveillance of mosquitoes and concomitant infectious agents is of great importance for prediction and prevention of mosquito-borne infectious diseases. Currently, morphological identification of mosquitoes is the traditional procedure. However, sequencing of specified genes or standard genomic regions, DNA barcoding, has recently been suggested as a global standard for identification and classification of many different species. Our aim was to develop a genetic method to identify mosquitoes and to study their relationship. Mosquitoes were captured at collection sites in northern Sweden and identified morphologically before the cytochrome c oxidase subunit I (COI) gene sequences of 14 of the most common mosquito species were determined. The sequences obtained were then used for phylogenetic placement, for validation and benchmarking of phenetic classifications and finally to develop a hierarchical PCR-based typing scheme based on single nucleotide polymorphism sites (SNPs) to enable rapid genetic identification, circumventing the need for morphological characterization. The results showed that exact phylogenetic relationships between mosquito taxa were preserved at shorter evolutionary distances, but at deeper levels, they could not be inferred with confidence using COI gene sequence data alone. Fourteen of the most common mosquito species in Sweden were identified by the SNP/PCR-based typing scheme, demonstrating that genetic typing using SNPs of the COI gene is a useful method for identification of mosquitoes with potential for worldwide application.

