ATL_FISHREF: A 12S mitochondrial reference dataset for metabarcoding Atlantic fishes frequently caught during scientific surveys in the Bay of Biscay

Abstract

The biodiversity crisis driven by anthropogenic pressures significantly threatens marine ecosystems. The rate of climate change and anthropogenic impacts outpace our traditional observation tools' capabilities, underscoring the urgency for new assessment methods. Environmental DNA (eDNA; DNA traces released by organisms) metabarcoding, a non-invasive method widely developed over the last decade, represents a promising biomonitoring tool thanks to a large spatio-temporal coverage, high detection of rare species and its time and cost-effectiveness. However, capturing fish diversity using eDNA requires genetic reference databases, currently lacking. Improving reference databases relies on opportunistic sampling enabling the reporting of sequences for new species. The data provided here consists of barcoding 86 species of fishes over the 12S mitochondrial DNA gene. We generated 156 sequences of the mitochondrial 12S gene adapted to the “Teleo” barcodes from fishes sampled in the Bay of Biscay (BoB; Northeast Atlantic, France) between 2017 and 2019. In addition, we provided each individual the barcode details (Genbank accession number, chromatograms), a photograph, 5 ecomorphological measures and 11 life-history traits documenting ecological functions (e.g., dispersion, habitat use, diet). Furthermore, we provided the sampling metadata (e.g., date, time, gear, coordinates, depth) and environmental variables measured in situ (e.g., conductivity, water/air temperature). This data set is valuable to improve the Northeast Atlantic eDNA genetic database, thus helping to better understand the effects of environmental forcing in the BoB, a transition zone housing mixed assemblages of boreal, temperate, and subtropical fish species susceptible to display variability in functional traits to adapt to changing conditions. The detailed Metadata for this abstract published in the Data Article section of the journal is available in MetaCat in JaLTER at https://jalter.diasjp.net/data/ERDP-2024-09.