Expanding eDNA resources for ornamental pest species detection

Dr Cecilia Villacorta Rath1, Professor Damien Burrows1

1James Cook University, Townsville, Australia

Biography:

Dr Cecilia Villacorta-Rath has led the establishment of northern Australia’s first purpose-built eDNA laboratory. She has vast experience engaging with end-users including government agencies, industry stakeholders, and non-government organisations. Cecilia's expertise includes translating emerging molecular technologies into operational monitoring tools that are relevant to policymakers and practitioners.

Abstract:

The ornamental fish trade is a pathway for introducing non-native freshwater fishes, creating a need for surveillance tools that detect incursions before populations become widespread. This study developed eDNA tools for ornamental fishes identified as posing a high establishment risk in Australia. Six targeted quantitative PCR assays were designed for Betta splendens, Cichla spp., Clarias batrachus, Poecilia latipinna, Xiphophorus helleri and Xiphophorus maculatus, together with a metabarcoding assay targeting Poeciliidae. Candidate assays were developed from mitochondrial sequence data and evaluated through in-silico and in-vitro testing using genomic DNA from target and non-target fishes. All targeted assays were specific to their target taxa. The Poeciliidae assay amplified target species earlier than the Australian native fishes tested. The assays were then applied to water samples collected across Queensland and the Northern Territory. Targeted screening detected X. maculatus at sites in the Townsville region, whereas the other five target taxa were not detected. The Poeciliidae metabarcoding assay excluded Australian native fishes during field-sample analysis but produced some species-level misassignments. These assays expand the molecular resources available for ornamental pest-fish surveillance and can support monitoring and early detection programs in northern Australia, although field validation and refinement of metabarcoding taxonomic assignments are recommended.