Multi-marker DNA metabarcoding for precise species identification in ichthyoplankton samples

Abstract

Ichthyoplankton monitoring is crucial for stock assessments, offering insights into spawning grounds, stock size, seasons, recruitment, and changes in regional ichthyofauna. This study evaluates the efficiency of multi-marker DNA metabarcoding using mitochondrial cytochrome c oxidase subunit I (COI), 12S rRNA and 16S rRNA gene markers, in comparison to morphology-based methods for fish species identification in ichthyoplankton samples. Two transects with four coastal distance categories were sampled along the southern coast of Portugal, being each sample divided for molecular and morphological analyses. A total of 76 fish species were identified by both approaches, with DNA metabarcoding overperforming morphology-75 versus 11 species-level identifications. Linking species-level DNA identifications with higher taxonomic morphological identifications resolved several uncertainties associated with traditional methods. Multi-marker DNA metabarcoding improved fish species detection by 20-36% compared to using a single marker/amplicon, and identified 38 species in common, reinforcing the validity of our results. PERMANOVA analysis revealed significant differences in species communities based on the primer set employed, transect location, and distance from the coast. Our findings underscore the potential of DNA metabarcoding to assess ichthyoplankton diversity and suggest that its integration into routine surveys could enhance the accuracy and comprehensiveness of fish stock assessments.