Universal closed-tube barcoding for monitoring the shark and ray trade in megadiverse conservation hotspots

Trade restrictions for many endangered elasmobranch species exist to disincentivise their exploitation and curb their declines. However, the variety of products and the complexity of import/export routes make trade monitoring challenging. We investigate the use of a portable, universal, DNA-based tool which would greatly facilitate in-situ monitoring. We collected shark and ray samples across the Island of Java, Indonesia, and selected 28 species (including 22 CITES-listed species) commonly encountered in landing sites and export hubs to test a recently developed real-time PCR single-assay originally developed for screening bony fish. We employed a deep learning algorithm to recognize species based on DNA melt-curve signatures. By combining visual and machine learning assignment methods, we distinguished 25 out of 28 species, 20 of which were CITES-listed. With further refinement, this method can provide a practical tool for monitoring elasmobranch trade worldwide, without the need for a lab or the bespoke design of species-specific assays. Highlights We applied a portable, universal, closed-tube DNA barcoding approach originally developed for bony fishes to distinguish between shark and ray species traded in Indonesia. We built a deep machine learning model to automatically assign species from the qPCR fluorescence spectra produced by two barcodes The model achieved 79.41% accuracy for classifying 28 elasmobranch species, despite the barcode regions being designed for teleost species This tool can serve as a potent single-assay in-situ diagnostic tool to regulate trade operations and it will be significantly enhanced by further optimisation of the barcode regions to fit elasmobranch DNA sequence variation