DNA reference libraries of French Guianese mosquitoes for barcoding and metabarcoding

Abstract : The mosquito family (Diptera: Culicidae) constitutes the most medically important group of arthropods because certain species are vectors of human pathogens. In some parts of the world, the diversity is so high that the accurate delimitation and/or identification of species is challenging. A DNA-based identification system for all animals has been proposed, the so-called DNA barcoding approach. In this study, our objectives were (i) to establish DNA bar-code libraries for the mosquitoes of French Guiana based on the COI and the 16S markers, (ii) to compare distance-based and tree-based methods of species delimitation to traditional taxonomy, and (iii) to evaluate the accuracy of each marker in identifying specimens. A total of 266 specimens belonging to 75 morphologically identified species or morphospecies were analyzed allowing us to delimit 86 DNA clusters with only 21 of them already present in the BOLD database. We thus provide a substantial contribution to the global mosquito bar-coding initiative. Our results confirm that DNA barcodes can be successfully used to delimit and identify mosquito species with only a few cases where the marker could not distinguish closely related species. Our results also validate the presence of new species identified based on morphology, plus potential cases of cryptic species. We found that both COI and 16S markers performed very well, with successful identifications at the species level of up to 98% for COI and 97% for 16S when compared to traditional taxonomy. This shows great potential for the use of metabarcoding for vector monitoring and eco-epidemiological studies.
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Soumis le : mercredi 24 juillet 2019 - 14:07:39
Dernière modification le : jeudi 25 juillet 2019 - 01:28:20

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  • HAL Id : hal-02193342, version 1

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Stanislas Talaga, Céline Leroy, Amandine Guidez, Isabelle Dusfour, Romain Girod, et al.. DNA reference libraries of French Guianese mosquitoes for barcoding and metabarcoding. PLoS ONE, Public Library of Science, 2017, 12 (12), pp.e0176993. ⟨hal-02193342⟩

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