ArticlePloS one2013
General patterns of diversity in major marine microeukaryote lineages.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Unveiling Protist Composition and Diversity Patterns With eDNA Metabarcoding: Comparing Short- and Long-Read Approaches.Ecology and evolution · 2026Article
- Protist diversity and community structure around the Xianbei Seamount in the South China Sea.Microbiology spectrum · 2026Article
- Unveiling the Microeukaryotic Landscape of the Red Coral Corallium rubrum Across the Northwestern Mediterranean Sea.Environmental microbiology reports · 2025Article
- Missing microbial eukaryotes and misleading meta-omic conclusions.Nature communications · 2024Article
- A new sampling device for metabarcoding surveillance of port communities and detection of non-indigenous species.iScience · 2024Article
- Disentangling the mechanisms shaping the surface ocean microbiota.Microbiome · 2020Article
- Tracing the Origin of Planktonic Protists in an Ancient Lake.Microorganisms · 2020Article
- Cryptic species in the parasitic Amoebophrya species complex revealed by a polyphasic approach.Scientific reports · 2020Article
- Marked changes in diversity and relative activity of picoeukaryotes with depth in the world ocean.The ISME journal · 2020Article
- Surface ocean metabarcoding confirms limited diversity in planktonic foraminifera but reveals unknown hyper-abundant lineages.Scientific reports · 2018Article
- Large-scale ocean connectivity and planktonic body size.Nature communications · 2018Article
- Copper Affects Composition and Functioning of Microbial Communities in Marine Biofilms at Environmentally Relevant Concentrations.Frontiers in microbiology · 2018Article
- Environmental Sequencing Provides Reasonable Estimates of the Relative Abundance of Specific Picoeukaryotes.Applied and environmental microbiology · 2016Article
- Large variability of bathypelagic microbial eukaryotic communities across the world's oceans.The ISME journal · 2016Article
- Chronic Polyaromatic Hydrocarbon (PAH) Contamination Is a Marginal Driver for Community Diversity and Prokaryotic Predicted Functioning in Coastal Sediments.Frontiers in microbiology · 2016Article
- Comparison of three clustering approaches for detecting novel environmental microbial diversity.PeerJ · 2016Article
- Diversity and distribution of unicellular opisthokonts along the European coast analysed using high-throughput sequencing.Environmental microbiology · 2015Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microeukaryotes have vital roles for the functioning of marine ecosystems, but still some general characteristics of their current diversity and phylogeny remain unclear. Here we investigated both aspects in major oceanic microeukaryote lineages using 18S rDNA (V4-V5 hypervariable regions) sequences from public databases that derive from various marine environmental surveys. A very carefully and manually curated dataset of 8291 Sanger sequences was generated and subsequently split into 65 taxonomic groups (roughly to Class level based on KeyDNATools) prior to downstream analyses. First, we calculated genetic distances and clustered sequences into Operational Taxonomic Units (OTUs) using different distance cut-off levels. We found that most taxonomic groups had a maximum pairwise genetic distance of 0.25. Second, we used phylogenetic trees to study general evolutionary patterns. These trees confirmed our taxonomic classification and served to run Lineage Through Time (LTT) plots. LTT results indicated different cladogenesis dynamics across groups, with some displaying an early diversification and others a more recent one. Overall, our study provides an improved description of the microeukaryote diversity in the oceans in terms of genetic differentiation within groups as well as in the general phylogenetic structure. These results will be important to interpret the large amount of sequence data that is currently generated by High Throughput Sequencing technologies.
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