4.6 Article

High-Resolution Melting (HRM) Analysis for Rapid Molecular Identification of Sparidae Species in the Greek Fish Market

Journal

GENES
Volume 14, Issue 6, Pages -

Publisher

MDPI
DOI: 10.3390/genes14061255

Keywords

mtDNA; barcoding; Pagrus; Dentex; fish mislabeling; authentication; fraud; COI; 16s; cytb

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In this study, a rapid method for species identification within the Sparidae family was developed using RFLPs, multiplex PCR, and HRM analysis of mtDNA regions. HRM analysis of cytb's 113 bp region and/or 16s's 156 bp region could differentiate P. pagrus and D. dentex samples from closely related species and P. pagrus samples from the Mediterranean Sea (compared to those from the eastern Atlantic) in raw or cooked samples.
The red porgy (Pagrus pagrus) and the common dentex (Dentex dentex) are Sparidae species of high commercial value, traded in the Greek market. In some cases, fish species identification from Greek fisheries is difficult for the consumer due to the strong morphological similarities with their imported counterparts or closely related species such as Pagrus major, Pagrus caeroleustictus, Dentex gibbosus and Pagellus erythrinus, especially when specimens are frozen, filleted or cooked. Techniques based on DNA sequencing, such as COI barcoding, accurately identify species substitution incidents; however, they are time consuming and expensive. In this study, regions of mtDNA were analyzed with RFLPs, multiplex PCR and HRM in order to develop a rapid method for species identification within the Sparidae family. HRM analysis of a 113 bp region of cytb and/or a 156 bp region of 16s could discriminate raw or cooked samples of P. pagrus and D. dentex from the aforementioned closely related species and P. pagrus specimens sampled in the Mediterranean Sea when compared to those fished in the eastern Atlantic. HRM analysis exhibited high accuracy and repeatability, revealing incidents of mislabeling. Multiple samples can be analyzed within three hours, rendering this method a useful tool in fish fraud monitoring.

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