title: Geographically widespread swordfish barcode stock identification: a case study of its application.
abstract: BACKGROUND
  The swordfish (Xiphias gladius) is a cosmopolitan large pelagic fish inhabiting tempered and tropical waters and it is a target species for fisheries all around the world. The present study investigated the ability of COI barcoding to reliably identify swordfish and particularly specific stocks of this commercially important species.
  
  
  METHODS
  We applied the classical DNA barcoding technology, upon a 682 bp segment of COI, and compared swordfish sequences from different geographical sources (Atlantic, Indian Oceans and Mediterranean Sea). The sequences of the 5' hyper-variable fragment of the control region (5'dloop), were also used to validate the efficacy of COI as a stock-specific marker.
  
  
  METHODS
  This information was successfully applied to the discrimination of unknown samples from the market, detecting in some cases mislabeled seafood products.
  
  
  CONCLUSIONS
  The NJ distance-based phenogram (K2P model) obtained with COI sequences allowed us to correlate the swordfish haplotypes to the different geographical stocks. Similar results were obtained with 5'dloop. Our preliminary data in swordfish Xiphias gladius confirm that Cytochrome Oxidase I can be proposed as an efficient species-specific marker that has also the potential to assign geographical provenance. This information might speed the samples analysis in commercial application of barcoding.
authors: Section of Biochemistry and Molecular Biology, Department of Biological, Geological and Environmental Sciences, University of Catania, National Institute of Biomembranes and Biosystems, Section of Catania, Catania, Italy.
authors: Anna Maria
authors: AM
authors: Pappalardo
authors: Francesca
authors: F
authors: Guarino
authors: Simona
authors: S
authors: Reina
authors: Angela
authors: A
authors: Messina
authors: Vito
authors: V
authors: De Pinto
mesh_terms: D000818:Animals; D016000:Cluster Analysis; D001330:Electronic Data Processing; D005843:Geography; D010473:Perciformes / Q000145:classification*; D010802:Phylogeny; D017747:Seafood