Biomonitoring of dinoflagellate communities in marine ecosystems is essential for efficient water quality management and limiting ecosystem disturbances. Current identification and monitoring of toxic dinoflagellates, which cause harmful algal blooms, primarily involves light or scanning electron microscopy; however, these techniques are limited in their ability to monitor dinoflagellates and plankton, leaving an incomplete analysis. In this study, we analyzed the species composition and seasonal distribution of the dinoflagellate communities in four Korean coastal regions using 18S rRNA amplicon sequencing. The results showed significantly high diversity in the dinoflagellate communities in all regions and seasons. Furthermore, we found seasonally dominant species and causative species of harmful algal blooms (Cochlodinium sp., Alexandrium sp., Dinophysis sp., and Gymnodinium sp.). Moreover, dominant species were classified by region and season according to the difference in geographical and environmental parameters. The molecular analysis of the dinoflagellate community based on metagenomics revealed more diverse species compositions that could not be identified by microscopy and revealed potentially harmful or recently introduced dinoflagellate species. In conclusion, metagenomic analysis of dinoflagellate communities was more precise and obtained results faster than microscopic analysis, and could improve the existing monitoring techniques for community analysis.
Keywords: dinoflagellates; metagenomics; monitoring; next-generation sequencing.