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In this study, a DNA mini-barcoding methodology was developed for the differentiation of species commonly found in canned tuna. Primers were designed to target a 236-base pair (bp) fragment of the mitochondrial control region (CR) and a 179-bp fragment of the first internal transcribed spacer region (ITS1). Phylogenetic analysis revealed the ability to differentiate 13 tuna species on the basis of the CR mini-barcode, except in a few cases of species introgression. Supplementary use of ITS1 allowed for differentiation of introgressed Atlantic bluefin tuna (Thunnus thynnus) and albacore tuna (Thunnus alalunga), while differentiation of introgressed Atlantic bluefin tuna and Pacific bluefin tuna (Thunnus orientalis) requires a longer stretch of the CR. After primer design, a market sample of 53 commercially canned tuna products was collected for testing. This mini-barcoding system was able to successfully identify species in 23 of the products, including albacore tuna, yellowfin tuna (Thunnus albacares), and skipjack tuna (Katsuwonus pelamis). One instance of mislabeling was detected, in which striped bonito (Sarda orientalis) was identified in a product labeled as tongol tuna (Thunnus tonggol). PCR amplification and sequencing was unsuccessful in a number of products, likely due to factors such as the presence of PCR inhibitors and DNA fragmentation during the canning process. Overall, CR and ITS1 show high potential for use in identification of canned tuna products; however, further optimization of the assay may be necessary in order to improve amplification and sequencing success rates.


NOTICE: this is the author’s version of a work that was accepted for publication in Food Analytical Methods. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was published in Food Analytical Methods, volume 9, issue 10, in 2016. DOI: 10.1007/s12161-016-0460-3

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