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Updated: Mar 19, 2026

A Standardized Procedure for Monitoring Harmful Algal Blooms in Chile by Metabarcoding Analysis
Published on: August 26, 2021
Development of a cost-effective metabarcoding strategy for analysis of the marine phytoplankton community
Tae-Ho Yoon1, Hye-Eun Kang2, Chang-Keun Kang3
1Interdiciplinary Program of Biomedical Engineering, Pukyong National University , Busan , Republic of Korea.
Abstract:
We developed a cost-effective metabarcoding strategy to analyze phytoplankton community structure using the Illumina MiSeq system. The amplicons (404-411 bp) obtained by end-pairing of two reads were sufficiently long to distinguish algal species and provided barcode data equivalent to those generated with the Roche 454 system, but at less than 1/20th of the cost. The original universal primer sequences targeting the 23S rDNA region and the PCR strategy were both modified, and this resulted in higher numbers of eukaryotic algal sequences by excluding non-photosynthetic proteobacterial sequences supporting effectiveness of this strategy. The novel strategy was used to analyze the phytoplankton community structure of six water samples from the East/Japan Sea: surface and 50 m depths at coastal and open-sea sites, with collections in May and July 2014. In total, 345 operational taxonomic units (OTUs) were identified, which covered most of the prokaryotic and eukaryotic algal phyla, including Dinophyta, Rhodophyta, Ochrophyta, Chlorophyta, Streptophyta, Cryptophyta, Haptophyta, and Cyanophyta. This highlights the importance of plastid 23S primers, which perform better than the currently used 16S primers for phytoplankton community surveys. The findings also revealed that more efforts should be made to update 23S rDNA sequences as well as those of 16S in the databases. Analysis of algal proportions in the six samples showed that community structure differed depending on location, depth and season. Across the six samples evaluated, the numbers of OTUs in each phylum were similar but their relative proportions varied. This novel strategy would allow laboratories to analyze large numbers of samples at reasonable expense, whereas this has not been possible to date due to cost and time. In addition, we expect that this strategy will generate a large amount of novel data that could potentially change established methods and tools that are currently used in the realms of oceanography and marine ecology.
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