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Single vs. Pooled: Metabarcoding Based Species Misrepresentation Detection of Sushi in Ontario by Sample Pooling Compared to Conventional DNA Barcoding

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Title: Single vs. Pooled: Metabarcoding Based Species Misrepresentation Detection of Sushi in Ontario by Sample Pooling Compared to Conventional DNA Barcoding
Author: Rathnayake, Sujani
Department: Department of Integrative Biology
Program: Integrative Biology
Advisor: Hanner, Robert
Abstract: Rising complexity of seafood supply chain necessitates enhanced efficacy and throughput of DNA barcode-based analytical techniques for seafood traceability. This study evaluated the applicability of sample pooling followed by metabarcoding for high-throughput seafood species identification and is the first ever application of this strategy for seafood traceability. Sushi samples from grocery and retail settings were initially tested by conventional DNA barcoding for species identity establishment prior to sample pooling. Species mislabeling, substitution and common name ambiguities were detected in sushi sold in restaurants and grocery stores in Ontario. Sample pooling strategy could establish species identities at variable levels of taxonomic hierarchy, including species and genera informative of species misrepresentation i.e., mislabeling, substitutions, and common name ambiguities. Nonetheless, key uncertainties such as primer universality, resolution, and reference database blind spots must be addressed prior to its broader applications at upper levels of seafood supply chain for testing large consignment of samples.
URI: https://hdl.handle.net/10214/27387
Date: 2023-01
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Related Publications: Rathnayake, Sujani; Chen, Shu; Hanner, Robert, 2022, "Single Vs. Pooled: Metabarcoding based species misrepresentation detection via sample pooling for efficacious traceability of sushi in Canada: Key methodological uncertainties compared to Conventional DNA Barcoding", https://doi.org/10.5683/SP3/DRZADW, Borealis, V2


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