ArticleScientific reports2024
Multi-marker DNA metabarcoding for precise species identification in ichthyoplankton samples.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- A mitochondrial DNA metabarcoding system based on tNGS enables multiplex identification of vertebrate species in samples containing degraded and mixed DNA.International journal of legal medicine · 2026Article
- Enhancing the 12S rRNA reference library of South African chondrichthyans to aid in eDNA metabarcoding.BMC zoology · 2026Article
- First description of the complete mitochondrial genomes of the species Amblyomma humerale and Amblyomma geayi (Acari: Ixodidae), Amazon, Pará, Brazil.Experimental & applied acarology · 2026Article
- From fish to invertebrates: multi-marker eDNA metabarcoding for monitoring wetland biodiversity and non-indigenous species in Macao SAR China.Scientific reports · 2026Article
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9 authors.
Funding
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.
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