DNA Barcoding Southwestern Atlantic Skates: A 20-Year Effort in Building a Species Identification Library

The skate fauna in the Southwest Atlantic Ocean (SWA; 34–55° S) is represented by ~32 species, many of which share external features that have led to misidentifications and deficient fishery statistics. The use of DNA barcoding to discriminate SWA skate species was explored after 20 years of surveys. COI sequences were subjected to distance-based neighbor-joining (NJ), maximum likelihood (ML), barcode index number (BIN), automatic barcode gap discovery (ABGD), and nucleotide diagnostic character (NDC) analyses. For widely distributed species, a haplotype network was built. Overall, 187 specimens and 31 egg cases from 26 skate species were barcoded. NJ and ML analyses showed that nearly all species exhibited unique barcodes or clusters of closely related haplotypes, except for Psammobatis normani/P. rudis and Dipturus trachyderma/D. argentinensis. The first pair was discriminated by NCD. BIN analysis recovered 17 groups, whereas ABGD recovered 23, better reflecting taxonomic diversity. In summary, 24 species were resolved by COI. Phylogeographic signals were observed for Amblyraja doellojuradoi and Zearaja brevicaudata. Compiling our results with data from BOLD, almost all the species occurring in the area possess barcodes, contributing to completing and curating the BOLD reference library, which constitutes an important tool for resolving taxonomic issues, tracing fishery products, and performing eDNA biomonitoring.

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Diversity
Published
2025-04-25
DOI
https://doi.org/10.3390/d17050311
Primary Topic
Identification and Quantification in Food
Type
article
Field-Weighted Citation Impact
0.00

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article

DNA Barcoding Southwestern Atlantic Skates: A 20-Year Effort in Building a Species Identification Library

Juan José Rosso, Valeria Gabbanelli, Victoria Malvina Lenain, Juan M. Dı́az de Astarloa et al.
Diversity
Identification and Quantification in Food
article

DNA Barcoding Southwestern Atlantic Skates: A 20-Year Effort in Building a Species Identification Library

Juan José Rosso, Valeria Gabbanelli, Victoria Malvina Lenain, Juan M. Dı́az de Astarloa, Ezequiel Mabragaña, Diego Martín Vazquez, Robert Hanner, Mariano González‐Castro, Florencia Matusevich, Sergio M. Delpiani
article en

Abstract

The skate fauna in the Southwest Atlantic Ocean (SWA; 34–55° S) is represented by ~32 species, many of which share external features that have led to misidentifications and deficient fishery statistics. The use of DNA barcoding to discriminate SWA skate species was explored after 20 years of surveys. COI sequences were subjected to distance-based neighbor-joining (NJ), maximum likelihood (ML), barcode index number (BIN), automatic barcode gap discovery (ABGD), and nucleotide diagnostic character (NDC) analyses. For widely distributed species, a haplotype network was built. Overall, 187 specimens and 31 egg cases from 26 skate species were barcoded. NJ and ML analyses showed that nearly all species exhibited unique barcodes or clusters of closely related haplotypes, except for Psammobatis normani/P. rudis and Dipturus trachyderma/D. argentinensis. The first pair was discriminated by NCD. BIN analysis recovered 17 groups, whereas ABGD recovered 23, better reflecting taxonomic diversity. In summary, 24 species were resolved by COI. Phylogeographic signals were observed for Amblyraja doellojuradoi and Zearaja brevicaudata. Compiling our results with data from BOLD, almost all the species occurring in the area possess barcodes, contributing to completing and curating the BOLD reference library, which constitutes an important tool for resolving taxonomic issues, tracing fishery products, and performing eDNA biomonitoring.

DiversityVol. 17(5)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), National University of Mar del Plata (AR), Austral University (AR), Universidad Nacional del Litoral (AR), Instituto Nacional de Limnología (AR), Institute of Marine and Coastal Research (AR), University of Guelph (CA)
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional de Mar del Plata
Openalex Percentile: Top 92%
Identification and Quantification in Food
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