Genomic databanks provide robust assessment of invasive mosquito movement pathways and cryptic establishment

BIOLOGICAL INVASIONS(2023)

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摘要
Biosecurity strategies that aim to restrict the spread of invasive pests can benefit from knowing where incursions have come from and whether cryptic establishment has taken place. This knowledge can be acquired with genomic databanks, by comparing genetic variation in incursion samples against reference samples. Here we use genomic databanks to characterise incursions of two mosquito species within Australia, and to observe how genomic tracing methods perform when databank samples have limited genetic differentiation and were collected tens of generations ago. We used a deep learning method to trace a 2021 invasion of Aedes aegypti in Tennant Creek, Northern Territory, to Townsville, Queensland, and to trace two years of Ae. albopictus incursions to two specific islands in the Torres Strait. Tracing had high precision despite 30–70 generations separating incursion and reference samples, and cross-validation of reference samples assigned them to the correct origin in 87% of cases. Similar precision was not achieved with PCAs, which performed particularly poorly for tracing when the invasion had been subject to strong drift effects. Targeted assays also provided additional information on the origin of the Tennant Creek Ae. aegypti , in this case by comparing Wolbachia infection data and mitochondrial DNA variation. Patterns of relatedness and inbreeding indicated that Tennant Creek was likely invaded by one family of Ae. aegypti , while Torres Strait incursions were independent and indicated no cryptic establishment. Our results highlight the value of genomic databanks that remain informative over years and for a range of biological conditions.
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关键词
Genomic databanks,Incursions,Deep learning,Biosecurity,Aedes mosquito,Wolbachia
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