Tracking genetic invasions: genome-wide SNPs reveal the source of pyrethroid-resistantAedes aegypti(yellow fever mosquito) incursions at international ports

Abstract

Biological invasions are increasing globally in number and extent despite efforts to restrict their spread. Knowledge of incursion pathways is necessary to prevent new invasions and to design effective biosecurity protocols at source and recipient locations. This study uses genome-wide single-nucleotide polymorphisms (SNPs) to determine the origin of 115 incursive Aedes aegypti (yellow fever mosquito) detected at international ports in Australia and New Zealand. We also genotyped mosquitoes at three point mutations in the voltage-sensitive sodium channel (Vssc) gene: V1016G, F1534C, and S989P. These mutations confer knockdown resistance to synthetic pyrethroid insecticides, widely used for controlling invertebrate pests. We first delineated reference populations using Ae. aegypti sampled from 15 locations in Asia, South America, Australia and the Pacific Islands. Incursives were assigned to these populations using discriminant analysis of principal components (DAPC) and an assignment test with a support vector machine predictive model. Bali, Indonesia, was the most common origin of Ae. aegypti detected in Australia, while Ae. aegypti detected in New Zealand originated from Pacific Islands such as Fiji. Most incursives had the same allelic genotype across the three Vssc gene point mutations, which confers strong resistance to synthetic pyrethroids, the only insecticide class used in current, widely-implemented aircraft disinsection protocols endorsed by the World Health Organisation (WHO). Additionally, all internationally-assigned Ae. aegypti had Vssc point mutations linked to pyrethroid resistance that are not found in Australian populations. These findings demonstrate that protocols for preventing introductions of invertebrates must consider insecticide resistance, and highlights the usefulness of genomic datasets for managing global biosecurity objectives.

Genomic databanks and targeted assays help characterise domestic mosquito incursions

“…Pest genomic databanks provide an increasingly popular means of investigating invasions and incursions (9)(10)(11)(12)(13)(14)(15)(16). The value provided by genomic databanks should continue to rise as costs of generating genome-scale data from large numbers of pests continue to decrease and as new genomic methods appropriate for pests are developed (44).…”

“…albopictus. Previous work on tracing these mosquitoes in Australia has focused on determining the country of origin of incursion samples collected at airports and seaports (13,15). In addition, some tracing of Ae.…”

“…While pathways may be easily inferred if incursions are detected on their vessel of entry, incursions that are detected later pose a greater challenge. Recent work using genomic databanks to trace incursions or recently established invasions indicates that these methods can reliably infer the most likely origin out of a set of reference populations (9)(10)(11)(12)(13)(14)(15)(16), and are particularly useful for tracing samples collected beyond border biosecurity. These methods compare genome-wide genetic variation in the incursion or invasion of interest against variation across reference samples, allowing the invasion to be linked to a population or a set of related populations of origin depending on the quality of the database.…”

Close kin dyads indicate intergenerational dispersal and barriers

“…Dispersal describes how organisms and their progeny come to occupy different locations, and it can refer to the movement of individuals or gametes (Howard 1960; Berry et al 2004; Royle and Young 2008) or to the intergenerational outcomes of this movement (Wright 1943; Rousset 2000). Approaches for assessing dispersal at the individual level include those that measure movement rates over key life history stages, such as through mark-release-recapture (MRR) methodologies (Royle and Young 2008), and those that assign dispersing seeds to parent plants (Smouse and Sork 2004) or dispersing individuals to their origins (Berry et al 2004; Schmidt et al 2019). Approaches that summarise dispersal at the population level often aim to estimate the intergenerational dispersal parameter, σ, the standard deviation of parent-offspring separation distances (Wright 1943; Broquet and Petit 2009).…”