Unsupervised machine learning and geometric morphometrics as tools for the identification of inter and intraspecific variations in the Anopheles Maculipennis complex

Bellin, Nicolò; Calzolari, Mattia; Magoga, Giulia; Callegari, Emanuele; Bonilauri, Paolo; Lelli, Davide; Dottori, M.; Montagna, Matteo; Rossi, Valeria

doi:10.1016/j.actatropica.2022.106585

Cited by 3 publications

(2 citation statements)

References 64 publications

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“…To determine population structure, we used UMAP software (with Russell-Rao distance metric) on the multi-sample VCF, followed by application of HDBSCAN (v0.8.28) 51 , 52 to determine sample clustering (see 53 – 55 for recent applications). This work was performed in python (v3.7.6), with scripts available from https://github.com/AntonS-bio/resistance-AedesAegypti .…”

Section: Methodsmentioning

confidence: 99%

Uncovering the genetic diversity in Aedes aegypti insecticide resistance genes through global comparative genomics

Spadar,

Collins,

Messenger

et al. 2024

Sci Rep

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Aedes aegypti is vector of many arboviruses including Zika, dengue, yellow fever, West Nile, and Chikungunya. Its control efforts are hampered by widespread insecticide resistance reported in the Americas and Asia, while data from Africa is more limited. Here we use publicly available 729 Ae. aegypti whole-genome sequencing samples from 15 countries, including nine in Africa, to investigate the genetic diversity in four insecticide resistance linked genes: ace-1, GSTe2, rdl and vgsc. Apart from vgsc, the other genes have been less investigated in Ae. aegypti, and almost no genetic diversity information is available. Among the four genes, we identified 1,829 genetic variants including 474 non-synonymous substitutions, some of which have been previously documented, as well as putative copy number variations in GSTe2 and vgsc. Global insecticide resistance phenotypic data demonstrated variable resistance in geographic areas with resistant genotypes. Overall, our work provides the first global catalogue and geographic distribution of known and new amino-acid mutations and duplications that can be used to guide the identification of resistance drivers in Ae. aegypti and thereby support monitoring efforts and strategies for vector control.

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Section: Methodsmentioning

confidence: 99%

Uncovering the genetic diversity in Aedes aegypti insecticide resistance genes through global comparative genomics

Spadar,

Collins,

Messenger

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…To determine population structure, we used UMAP software (with Russell-Rao distance metric) on the multi-sample VCF, followed by application of HDBSCAN (v0.8.28) (51,52) to determine sample clustering (see (53)(54)(55) for recent applications). This work was performed in python (v3.7.6), with scripts available from https://github.com/AntonS-bio/resistance-AedesAegypti.…”

Section: Population Genetics Analysismentioning

confidence: 99%

Uncovering the genetic diversity inAedes aegyptiinsecticide resistance genes through global comparative genomics

Spadar,

Collins,

Messenger

et al. 2024

Preprint

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Insecticides are essential to control the transmission of vector-borne diseases to humans and animals, but their efficacy is being threatened by the spread of resistance across multiple medically important mosquito species. An example of this isAedes aegypti- a major vector of arboviruses, including Zika, dengue, yellow fever, West Nile, and Chikungunya, with widespread insecticide resistance reported in the Americas and Asia, while data from Africa is more limited. Here we investigate the global genetic diversity in four insecticide resistance associated genes:ace-1,GSTe2,rdlandvgsc.Apart fromvgsc, the other genes have been less investigated inAe. aegypti, and limited genetic diversity information is available. We explore a large whole-genome sequencing dataset of 729Ae. aegyptiacross 15 countries including nine in Africa. Among the four genes, we identified 1,829 genetic variants including 474 non-synonymous substitutions, as well as putative copy number variations inGSTe2andvgsc. Among these are many previously documented insecticide resistance mutations which were present at different frequencies and combinations depending on origin of samples. Global insecticide resistance phenotypic data demonstrated variable resistance in geographic areas with resistant genotypes. These warrant further investigation to assess their functional contribution to insecticide resistant phenotypes and their potential development into genetic panels for operational surveillance. Overall, our work provides the first global catalogue and geographic distribution of known and new amino-acid mutations and duplications that can be used to guide the identification of resistance drivers inAe. aegyptiand thereby support monitoring efforts and strategies for vector control.

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Applications of 3D modeling in cryptic species classification of molluscs

Yan,

Hu,

Dong

2024

Mar Biol

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Unsupervised machine learning and geometric morphometrics as tools for the identification of inter and intraspecific variations in the Anopheles Maculipennis complex

Cited by 3 publications

References 64 publications

Uncovering the genetic diversity in Aedes aegypti insecticide resistance genes through global comparative genomics

Uncovering the genetic diversity in Aedes aegypti insecticide resistance genes through global comparative genomics

Uncovering the genetic diversity inAedes aegyptiinsecticide resistance genes through global comparative genomics

Applications of 3D modeling in cryptic species classification of molluscs

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