A metabarcode based (species) inventory of the northern Adriatic phytoplankton.
Lana GrižančićAna BaričevićMirta Smodlaka TankovićIvan VlašičekMia KnjazIvan PodolšakTjaša KogovšekMartin Andreas PfannkuchenDaniela Marić PfannkuchenPublished in: Biodiversity data journal (2023)
This study aimed to report an up-to-date list of the phytoplankton taxonomic richness and phylogenetic relationships in the eastern northern Adriatic, based on sequence variability of barcoding genes resolved with advanced molecular tools, namely metabarcoding. Here, metabarcoding is used to complement standardised light microscopy to advance conventional monitoring and research of phytoplankton communities for the purpose of assessing biodiversity and the status of the marine environments. Monthly two-year net sampling targeted six phytoplankton groups including Bacillariophyceae (diatoms) and Chrysophyceae (golden algae) belonging to Ochrophyta, Dinophyceae (dinoflagellates), Cryptophyceae (cryptophytes), Haptophyta (mostly coccolithophorids) and Chlorophyta with Prasinophyceae (prasinophytes) and Chlorophyceae (protist green algae). Generated sequence data were taxonomically assigned and redistributed in two kingdoms, five classes, 32 orders, 49 families and 67 genera. The most diverse group were dinoflagellates, comprising of 34 found genera (48.3%), following by diatoms with 23 (35.4%) and coccolithophorids with three genera (4.0%). In terms of genetic diversity, results were a bit different: a great majority of sequences with one nucleotide tolerance (ASVs, Amplicon sequence variants) assigned to species or genus level were dinoflagellates (83.8%), 13.7% diatoms and 1.6% Chlorophyta, respectively. Although many taxa have not been detected that have been considered as common in this area, metabarcoding revealed five diatoms and 20 dinoflagellate genera that were not reported in previous checklists, along with a few species from other targeted groups that have been reported previously. We here describe the first comprehensive 18S metabarcode inventory for the northern Adriatic Sea.
Keyphrases
- genetic diversity
- water quality
- cancer therapy
- single molecule
- south africa
- amino acid
- copy number
- psychometric properties
- high resolution
- single cell
- big data
- genome wide
- high throughput
- gene expression
- machine learning
- mass spectrometry
- artificial intelligence
- bioinformatics analysis
- deep learning
- genome wide identification