Ehlers, G. | bioRxiv Science

bioRxiv2022

Genomic databanks and targeted assays help characterise mosquito incursions within Australia

Biosecurity strategies that aim to restrict the spread of invasive pests can benefit from knowing where new incursions have come from. This knowledge can be acquired using genomic databanks, by comparing genetic variation in incursion samples against reference samples. Here we use genomic databanks to investigate domestic incursions of two mosquito species in Australia, and assess the performance of genomic tracing methods when databank samples were collected some time ago or are genetically similar. 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. We observed high precision of tracing despite 30-70 generations separating incursion and reference samples. 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, whereas Torres Strait incursions involved distinct kinship groups. Our results highlight the value of genomic databanks that remain informative over years and for a range of biological conditions, and demonstrate how additional targeted assays (e.g. Wolbachia) can improve inferences. Key MessageO_LIGenomic tracing can provide valuable information on pest incursions and new invasions. C_LIO_LIEvolution will lead to increasing differences between databanks and extant populations. C_LIO_LIWe tested how well genomic databanks could trace incursions sampled 30-70 generations later and where genetic differentiation was low. C_LIO_LIWe show that tracing methods are robust for a wide range of conditions, and report specific incursion origins for two Aedes species. C_LIO_LIOur results suggest that genomic databanks will remain informative over years and for a range of invasive systems. C_LI

genomics↗

bioRxiv2020

Spatial population genomics of a recent mosquito invasion

Population genomic approaches can characterise dispersal across a single generation through to many generations in the past, bridging the gap between individual movement and intergenerational gene flow. These approaches are particularly useful when investigating dispersal in recently altered systems, where they provide a way of inferring long-distance dispersal between newly established populations and their interactions with existing populations. Human-mediated biological invasions represent such altered systems which can be investigated with appropriate study designs and analyses. Here we apply temporally-restricted sampling and a range of population genomic approaches to investigate dispersal in a 2004 invasion of Aedes albopictus (the Asian tiger mosquito) in the Torres Strait Islands (TSI) of Australia. We sampled mosquitoes from 13 TSI villages simultaneously and genotyped 373 mosquitoes at genome-wide single nucleotide polymorphisms (SNPs): 331 from the TSI, 36 from Papua New Guinea (PNG), and 4 incursive mosquitoes detected in uninvaded regions. Within villages, spatial genetic structure varied substantially but overall displayed isolation by distance and a neighbourhood size of 232-577. Close kin dyads revealed recent movement between islands 31-203 km apart, and deep learning inferences showed incursive Ae. albopictus had travelled to uninvaded regions from both adjacent and non-adjacent islands. Private alleles and a coancestry matrix indicated direct gene flow from PNG into nearby islands. Outlier analyses also detected four linked alleles introgressed from PNG, with the alleles surrounding 12 resistance-associated cytochrome P450 genes. By treating dispersal as both an intergenerational process and a set of discrete events, we describe a highly interconnected invasive system.

genomics↗