Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Novel diversity within marine Mamiellophyceae (Chlorophyta) unveiled by metabarcoding


Mamiellophyceae (unicellular green algae) are a key phytoplankton group in coastal waters. Although extensively studied over the last 20 years, the overall oceanic distribution of the major species/clades is still poorly known. To address this problem, we analyzed the 2014 Ocean Sampling Day (OSD) metabarcoding dataset providing sequences from the V4 hypervariable region of the 18S rRNA gene for 157 samples collected at 143 mostly coastal stations. Mamiellophyceae were found at nearly all OSD stations and represented 55% of the green microalgae (Chlorophyta) reads. We performed phylogenetic analyses of unique OSD metabarcodes (amplicon single variants, ASVs) and GenBank reference sequences from cultures and from the environment, focusing on the four most represented genera: Ostreococcus (45% of the Mamiellophyceae reads), Micromonas (34%), Bathycoccus (10%) and Mantoniella (8.7%). These analyses uncovered novel diversity within each genus except Bathycoccus. In Ostreococcus, a new clade (E) was the second most represented clade after Ostreococcuslucimarinus”. Micromonas could be separated into nine clades, exceeding the six species and candidate species already described. Finally, we found two new environmental clades within Mantoniella. Each Mamiellophyceae clade had a specific distribution in the OSD dataset suggesting that they are adapted to different ecological niches.


In marine waters, the accepted paradigm is that the so-called “red” lineage (mainly diatoms and dinoflagellates) is dominant, while the “green” lineage (land plants) is dominant in terrestrial environments1. These two lineages are differentiated by the evolutionary origin of their chloroplasts: those of the “green” lineage are surrounded in most cases by two membranes, which is evidence of a single endosymbiotic event, and their major photosynthetic pigments are chlorophyll a and b1. Studies in coastal waters performed with both microscopic and molecular techniques found that the “green” lineage, which is mainly represented by Chlorophyta among unicellular protists, can be abundant in these ecosystems, especially among the smaller size fractions2,3,4. Metabarcoding studies following the development of high-throughput sequencing (HTS) have confirmed the importance of Chlorophyta in marine waters5,6.

Mamiellophyceae consists of three orders: Mamiellales, Dolichomastigales and Monomastigales7. Monomastigales are confined to freshwater environments, while Dolichomastigales, although quite diversified in marine waters8,9, are a minor component of Mamiellophyceae in coastal waters. In contrast, Mamiellales, composed of two families, Mamiellaceae and Bathycoccaceae, host some of the most common Chlorophyta microalgae such as the widely distributed Micromonas, the smallest known eukaryote Ostreococcus and the coccoid Bathycoccus7. Within Mamiellaceae, Micromonas pusilla10 was recently split into four species, namely, Micromonas bravo (previously clade B.E.3), Micromonas commoda (previous clade A.ABC.1–2), Micromonas polaris (previously clade B arctic), Micromonas pusilla (previously clade C.D.5), and two clades described as candidate species 1 (clade B._.4) and candidate species 2 (clade B warm)11. Within the genus Mantoniella, only four species have been described: the widely distributed Mantoniella squamata3,12, first described as Micromonas squamata13, Mantoniella antarctica14, and two newly described species Mantoniella baffinensis and Mantoniella beaufortii that appear restricted to arctic waters15. Within Bathycoccaceae, four Ostreococcus clades have been delineated16: Ostreococcus tauri17 and Ostreococcus mediterraneus18, both of which were formerly described, and Ostreococcuslucimarinus” (clade A) and clade B, both of which lack formal taxonomic description. Analyses of pigment content and response to light levels allowed two broad ecotypes to be distinguished: strains adapted to high light (O. tauri,O. mediterraneus and O. “lucimarinus”) and those adapted to low light (Ostreococcus clade B)19. The second genus within Bathycoccaceae hosts a single species, Bathycoccus prasinos20. No clades can be delineated within this species based on 18S rRNA gene sequences from cultures and the environment. However, divergence in ITS sequences suggests that B. prasinos probably consists of two different species21,22.

The European Ocean Sampling Day (OSD) project sampled global coastal waters in 2014 at approximately the summer solstice (21 June) with the aim of analyzing the diversity and distribution of marine microorganisms23 especially in coastal waters using 18S rRNA metabarcodes (V4 and V9 hypervariable regions)24. This dataset allowed the distribution of fourteen classes of Chlorophyta to be determined25. Mamiellophyceae7, the most prevalent class in all coastal environments26, did not show any geographic distribution patterns or environmental preference25.

The present paper uses the OSD V4 datasets to analyze the taxonomic diversity and global distribution of four major Mamiellophyceae genera: Ostreococcus, Micromonas, Bathycoccus and the less studied Mantoniella. Our analyses reveal the existence of novel clades within Ostreococcus, Micromonas and Mantoniella and that most species/clades have specific oceanic distributions.

Material and Methods

The OSD consortium provided two metabarcoding datasets for 2014 using the V4 region of the 18S rRNA gene: the LGC dataset (sequenced by LGC Ltd.) consisting of 157 water samples from 143 stations (see filtered through 0.22 μm pore size Sterivex filters without prefiltration and the Life Watch (LW) dataset consisting of a subset of 29 water samples filtered through 0.8 μm pore size polycarbonate membranes without prefiltration. The extraction, PCR and sequencing protocols were described previously24,25. In brief, the LGC and LW data originated from the same water samples but were processed independently for filtration, DNA extraction, PCR amplification and sequencing (both Illumina 2 × 250 bp). The LGC and LW datasets contained approximatively 5 and 9 million V4 sequences, respectively, resulting in higher coverage for the LW dataset.

The LGC and LW datasets ( were analyzed with the same pipeline using mothur software v. 1.35.127. Reads were filtered to keep only sequences without ambiguities (N) and longer than 300 bp. Reads were aligned with SILVA seed release 123 reference alignment28 and corrected by hand to remove gaps at the beginning and at the end of alignments. The aligned datasets were filtered by removing columns containing only insertions. Chimeras were detected using Uchime v. 4.2.4029 as implemented in mothur. Representatives of sets of identical sequences, referred to here as Amplicon Single Variants (ASVs, following Callahan et al.30) were assigned using the Wang classifier as implemented in mothur and the PR2 reference database31 version 4.2 ( for which the Chlorophyta sequences had been recently curated6.

To confirm the assignation and explore the genetic diversity of Mamiellophyceae, ASVs from Bathycoccus, Micromonas, Ostreococcus and Mantoniella represented by more than 200 reads in either the LW or LGC dataset were selected. These selected ASVs were aligned to GenBank reference sequences using MAFFT v. 7.01732. Maximum likelihood (ML) phylogenies were built using FastTree v. 1.033,34 as implemented in Geneious v. 7.1.935. Bayesian phylogenies were built with MrBayes v. 3.2.636. implemented in Geneious. Clades were defined by both the presence of clear signatures in the alignments and phylogenetic features6,37,38: a clade had to be monophyletic, found with the two different construction methods (i.e., ML and Bayesian) and supported by bootstrap values greater than 70 %.

We selected a subset of 92 samples with more than 100 Mamiellophyceae reads (Table S1) to compute the relative abundance of selected ASVs using R software version 3.3.1 ( Graphics were created using the R packages ggplot2, ComplexHeatmap39 and treemapify.

Results and Discussion

We analyzed unique sequences (ASVs30) of two separate OSD datasets: LGC and LW. We focused on the LGC dataset which encompasses a much larger number of samples than the LW dataset which corresponds to a subset of the OSD samples that were processed in a completely independent manner compared to the LGC dataset (differences in filtration, DNA extraction, PCR and Illumina sequencing). The LW dataset was mainly used to confirm that the LGC ASVs were not artifacts by verifying that any major LGC ASV corresponded to an LW ASV with a strictly identical sequence.

Mamiellophyceae represented 55% of the Chlorophyta reads found in the OSD 2014 surface samples25. Overall 10,447 Mamiellophyceae ASVs (97.5% of the ASVs) were assigned to seven genera, while the other ASVs were classified only at the family or order level. Four genera were clearly dominant: Ostreococcus, Micromonas, Bathycoccus and Mantoniella, the former two having almost equal contributions (Fig. 1). We decided to focus on 92 samples having at least 100 Mamiellophyceae reads and on 23 major LGC ASVs for the four main genera that were represented by at least 200 reads (Table 1). These major ASVs corresponded to 68% of the Mamiellophyceae reads. Among these ASVs, the one assigned to B. prasinos was the most widely distributed followed by two assigned to Micromonas clades and one assigned to O. “lucimarinus” (Fig. S1).

Figure 1
figure 1

Treemap of the number of reads for Mamiellophyceae genera and clades for the OSD2014 LGC dataset. Only selected ASVs with more than 200 total reads (Table 1) and stations with more than 100 Mamiellophyceae reads (Table S1) were taken into account.

Table 1 Major Mamiellophyceae amplicon single variants (ASVs) from the LGC and LW datasets: taxonomic assignation, total abundance and representative sequences name.


In total, 4,223 ASVs from the LGC dataset were assigned to the genus Ostreococcus, among which 10 had more than 200 reads (Table 1). For each of these abundant LGC ASVs, we found a corresponding ASV in the LW dataset. These sequences constituted five clades (Fig. 2A), four of which were previously described and a new one that we named clade E, following the previous conventions for naming Ostreococcus clades16. The same tree topology was recovered with ML and Bayesian methods. Alignments (Fig. 2B) confirmed that the V4 region exhibited clear signatures delineating the five Ostreococcus clades. In this region, the genetic variation between clades (Table S2) was too low to discriminate the different clades when V4 operational taxonomic units (OTUs) are built with a 99% identity threshold, except for O. mediterraneus (98.3%). In terms of overall distribution, Ostreococcus was completely absent from high latitudes beyond 65° N (Iceland, Greenland and Nunavut, Fig. 3). O. “lucimarinus” was the most widely distributed (Fig. S1). In general none of the different Ostreococcus species/clades seemed to co-occur, with the exception of O. tauri and O. “lucimarinus” and to a lesser extent, clades B and E (Fig. S2).

Figure 2
figure 2

Phylogenetic diversity within the genus Ostreococcus. (A) Phylogenetic tree of 26 Ostreococcus sequences from the V4 region of the 18S rRNA gene (FastTree). The tree was rooted with B. prasinos. Only ML bootstrap values higher than 70% are represented. Bayesian posterior probabilities are in bold. ASVs are in bold: black for the LGC dataset and gray for the LW dataset. Only ASVs represented by more than 200 reads were taken into account. Environmental GenBank sequences are in blue. (B) Alignment of 26 Ostreococcus V4 regions: the alignment is 341 bp long, but only the main signatures are shown (between positions 20 and 140 of the original alignment).

Figure 3
figure 3

Distribution of the major Ostreococcus ASVs for OSD2014 (LGC). The three major O. tauri ASVs have been pooled together. Circle surface corresponds to the percentage of ASV reads relative to the total number of Mamiellophyceae reads. Samples for which the contribution of the ASV was lower than 1% or where it was absent are represented by blue crosses. A zoomed-in map of European waters is provided in Fig. S3.

Three ASVs were assigned to the first described species of Ostreococcus, O. tauri, with a number of reads ranging from 1,000 to 3,500 (Table 1). These ASVs did not form a monophyletic clade in either ML and Bayesian tree (Fig. 2A). The two major ASVs (ASV_LGC_00012 and ASV_LGC_00013) were closely related to the 18S rRNA sequence recovered from the genome of O. tauri (GQ426344). The third ASV (ASV_LGC_00018) was identical to the sequence with accession number Y15814 which was obtained more than 20 years ago for the type strain of O. tauri isolated from the Thau Lagoon on the French Mediterranean coast17. The V4 alignment (Fig. 2B) revealed two signatures for O. tauri. Ostreococcus tauri ASVs represented more than 1% of Mamiellophyceae reads at 35 stations and were abundant on the East Coast of the USA, and in the Baltic Sea, the Adriatic Sea (Venice Lagoon), the Black Sea and Uruguay lagoons (Figs 3 and S3). Some of these samples corresponded to brackish environments (e.g., a salinity 9.0, 7.4 and 7.2 at OSD35, OSD36 and OSD186, respectively, all in Chesapeake Bay, USA or of 24 at OSD39 in Charleston Harbor, USA) which were similar to those from Thau Lagoon where salinity is highly variable from 24 to 3817. Surprisingly O. tauri was absent from the western Mediterranean Sea despite the fact that strains have been isolated from there18. The existence of several ASVs suggests that O. tauri might be a complex of species, that need to be better distinguished and that could be adapted to different ranges of salinity.

Two major ASVs (ASV_LGC_00002 and ASV_LGC_00025) were assigned to O. “lucimarinus”, which was initially described as a high-light-adapted clade19, corresponding to 23,119 reads (Table 1) and representing up to 64% of the Mamiellophyceae reads off South Africa (Robben Island, OSD133). This clade dominated Atlantic and North Sea European coastal stations (Belgium, OSD183: 62% and OSD184: 44%; Portugal OSD115: 53%) and represented 40% of Mamiellophyceae reads at one of the three Azores stations (OSD98, Fig. 3). In contrast, O. “lucimarinus” was almost absent from the Mediterranean Sea and tropical waters (Figs 3 and S3). This distribution is consistent with the clade being a cold mesotrophic coastal clad, based on observations by qPCR (clade OI according to Demir-Hilton et al.40, see below).

A single ASV was assigned to Ostreococcus clade B, initially described as a low-light-adapted clade19, representing 6,207 reads, and accounting for 62% of the Mamiellophyceae reads off Panama (OSD51, Fig. 3). Clade B constituted more than 10% of the Mamiellophyceae reads at seven tropical and subtropical stations from various oceans (OSD60 in South Carolina; OSD25, OSD37 and OSD51 in Florida; OSD95 in Singapore; OSD122 in the Red Sea; OSD147 in Sri Lanka, Fig. 3), which is consistent with previous results obtained by qPCR which detected clade B at warm oligotrophic sites40,41.

The novel Ostreococcus clade E was represented by a single ASV in the LGC dataset (22,720 reads) and an identical sequence was also found in the LW dataset, suggesting that the detection of this clade was not an artefact. The clade E sequence is very similar to that of clade B, with two clear bp differences (Fig. 2B), and is 100% similar to a single sequence available from GenBank (accession number MH008654) also obtained by Illumina sequencing from South China Sea waters42. The V4 sequence of clade E is 99.4% similar to that of clade B, such that these two clades may have been lumped together in many metabarcoding studies that considered OTUs rather than ASVs. Clade E could be locally dominant in OSD samples representing up to 70% of the Mamiellophyceae reads (OSD111, off Portugal). The clade dominated coastal warm temperate stations (Fig. 3) on both sides of the Atlantic Ocean (Southern USA: OSD39, OSD58 and OSD143; Portugal: OSD81, OSD111, OSD117 and OSD153; and France: OSD154) and the Mediterranean Sea (Adriatic Sea off Venice: OSD69). It is surprising that no culture has been obtained for this new clade, but this absence could be due to the fact that the clade requires specific conditions to grow.

Finally, two ASVs with a low number of reads (369 and 248, in the LGC dataset, Table 1) were assigned to the species O. mediterraneus. These ASVs were found only in a lagoon along the coast of Uruguay (5% and 6% of Mamiellophyceae reads at OSD149 and OSD150, respectively, Fig. 3). This distribution is consistent with the fact that almost all strains of O. mediterraneus have been isolated from coastal lagoons along the Mediterranean Sea coast18, suggesting that this species is restricted to very specific environments with fluctuating salinity. Interestingly, a sequence matching O. mediterraneus has also been found in the freshwater Lake Taihu (China)43.

Two sets of qPCR primers and probes were previously designed40 based on available V4 sequences from strains in culture in order to discriminate two Ostreococcus groups (OI and OII). The OI set targets O. “lucimarinus” but also recognizes O. tauri40, which has two mismatches with the reverse primer (Fig. S4), while the OII group targets Ostreococcus clade B. Interestingly the new Ostreococcus clade E has four mismatches with set OI (one with the forward primer, one with the probe and two with the reverse primer) and two mismatches with set OII (one with the forward primer and one with the probe). Since some of these mismatches are located on the 3′ end of the forward primer (Fig. S4), these sets may be unable to recognize Ostreococcus clade E. If strains from Ostreococcus clade E become available, it would probably be necessary to design new qPCR sets specific to each of the Ostreococcus species/clades, which seem to have different distributions (Fig. 3).


A total of 4,285 unique OSD LGC sequences were assigned to the genus Micromonas, with 10 corresponding to more than 200 reads. Phylogenetic analysis and 18S V4 signatures allowed these sequences to be divided into 9 major clades (Fig. 4) corresponding to the species, candidate species and clades recently described by Simon et al.11, with the exception of a new subarctic clade not seen previously. M. commoda and M. bravo were each divided further into two subclades (Table 2). The clade nomenclature of Micromonas has been very confusing, with at least 4 different conventions used (Table 2). We decided to adopt a novel clade nomenclature that relies on the original three clades of Guillou et al.16 (A, B, and C), appending a number for subclades (e.g., B3, B4, B5). This scheme has been used for various taxonomic groups and allows new clades and subclades to be added easily26.

Figure 4
figure 4

Phylogenetic diversity within the genus Micromonas. (A) Phylogenetic tree of 39 Micromonas sequences from the V4 region of the 18S rRNA gene (FastTree). The tree was rooted with Mamiellales (RCC391, AY425321 and Mamiella gilva, FN562450). Legend as in Fig. 2. (B) Alignment of 39 Micromonas V4 regions: the alignment is 327 bp long, but only the main signatures are shown (between positions 50 and 150 of the original alignment).

Table 2 Equivalence between the clade nomenclature for the genus Micromonas in this paper compared to those of Guillou et al.16, Slapeta et al.48, Worden72 and Simon et al.11.

A well-supported tree topology was recovered with both ML and Bayesian methods. The genetic divergence between clades was greater than 1% for almost all the clade pairs (Table S3), allowing all clades to be distinguished with the 99% identity threshold commonly used in metabarcoding studies, except for M. commoda A1 and A2 (99.4% identity), M. bravo B1 and B2 (99.3% identity), M. polaris and the new clade B3 (99.2%). M. bravo B2 was present in the largest number of samples (76, Fig. S1A). Most species/clades did not co-occur, with the exception of M. bravo B1 and B2 (Fig. S2).

The major Micromonas ASV, represented by 28,810 reads, was assigned to M. bravo B2 (Fig. 4). M. bravo is a newly described species11 that was previously part of the B clade16. This ASV represented up to 60% of the Mamiellophyceae reads (Figs 5 and S5) in the Black Sea (OSD131) and off Portugal (OSD102). This ASV dominated most Mediterranean Sea stations, some North European stations and, to a lesser extent, some Pacific stations (14% off California at OSD43 and 28% at Hawaii OSD144). This ASV was the only Micromonas ASV that represented more than 10% of Mamiellophyceae reads off Japan (29% for OSD124). M. bravo B1 ASV (5,459 reads) represented more than 10% of Mamiellophyceae reads at three stations along the European coast (in particular 47% in the English Channel off Plymouth, OSD1).

Figure 5
figure 5

Distribution of the major Micromonas ASVs for OSD2014 (LGC). Legend as in Fig. 3. A zoomed-in map of European waters is provided in Fig. S5.

Two LGC ASVs with a single base pair difference (Fig. 4B) were closely related to the reference sequence of “candidate species 2” from Simon et al.11 and of “clade VI” from Lin et al.44. These ASVs are referred to here as Micromonas sp. clade B5. These two ASVs (6,296 reads) accounted for more than 10% of the Mamiellophyceae reads at eight stations in tropical or warm waters (Fig. 5): at the three Hawaii stations (OSD56, OSD57, and OSD144), off Florida (OSD37), off Portugal (OSD101), off Singapore (OSD95) and in Venice Lagoon (OSD69 and OSD70). This distribution was consistent with data from available GenBank sequences11: one representative strain was isolated in the Mediterranean Sea in summer (RCC1109) and environmental clones weren recovered in the Red Sea45, in the South China Sea (“unknown clade”46) and off Taiwan (Micromonas clade VI44).

M. commoda A2 ASV (10,787 reads) represented more than 1% of the Mamiellophyceae reads at 57 stations (Fig. S1) and up to 35% off the Atlantic coast of Canada (OSD152). This ASV was found in the North Atlantic up to Iceland and off New Zealand (Figs 5 and S5). In contrast, this ASV was almost completely absent from the Mediterranean Sea as well as from tropical stations. The frequency of M. commoda A1 (5,465 reads) was above 1% at a much lower number of stations (16, Fig. 1) and accounted for up to 40% of the Mamiellophyceae reads off Sri Lanka (OSD147). M. commoda A1 was distributed in tropical and subtropical waters (Figs 5 and S5), in particular, off Florida, Singapore and Hawaii as well as in the Eastern Mediterranean Sea off Israel. M. commoda was described by Van Baren et al.47 who mentioned only that this species had not been recorded yet at high latitudes (beyond 60 North or 60 South). The species was then revised by Simon et al.11, who described the distribution of this species as ubiquitous based on available GenBank sequences. The genetic variability within this species had already been highlighted previously48,49 and was confirmed by the OSD data since the two subclades A1 and A2 had clearly distinct distributions. Simon et al.11 proposed the hypothesis that speciation events may be ongoing within M. commoda.

The ASV (1,616 reads) corresponding to Micromonas sp. clade B4 (“candidate species 1” according to Simon et al.11) reached a frequency of 15% off Florida (OSD29) and was found in rather warm waters (off Hawaii, Israel, and Morocco, Fig. 5), which matches the distribution of sequences available in GenBank that had been previously recovered from the Mediterranean and Red Seas as well from the Pacific Ocean11.

M. polaris ASV (2,200 reads) was the major Mamiellophyceae contributor (Fig. 5) at two stations in Arctic waters (73% in Nunavut OSD105, 66% in Fram Strait OSD146) and was also present in the Gulf of Finland (OSD30). This pattern is consistent with current knowledge of this species. M. polaris was first isolated from the Arctic Ocean50 and shown to be the dominant picoeukaryote in the Beaufort Sea in the summer51. This ASV was also recently recorded in the Southern Ocean52, although its presence appears to be less prevalent since it is absent from environmental Antarctic clone libraries6. A new Micromonas clade closely related to M. polaris (B3, 1,096 reads) had a maximum contribution off Canada (32% in Bedford Basin OSD152) and represented more than 10% of Mamiellophyceae reads at four subarctic stations off Maine and Iceland as well as at a temperate location off the UK coast in the North Sea (Fig. 5). This ASV is 100% similar to GenBank sequences recently obtained in the White Sea53.

Finally, the ASV corresponding to the first described Micromonas species, M. pusilla, was found at low abundance (1,259 reads) mostly in temperate locations (Fig. 5) corresponding to the environment from which it was initially described and isolated (e.g. CCMP490 isolated from Woods Hole, USA, and CCMP491 from the English Channel, UK48).


The ASV corresponding to Bathycoccus was both the most abundant (24,391 reads) and the most prevalent, accounting for more than 1% of the Mamiellophyceae reads at 72 stations (Fig. S1) distributed all over the coastal ocean from tropical to polar waters (Figs 6 and S6). This worldwide distribution of the genus matches what has been observed based on the Tara Oceans dataset21 where the metagenome of Bathycoccus was recovered at a wide range of stations. Bathycoccus is now known to be composed of two cryptic species with identical 18S rRNA sequences (that therefore cannot be distinguished in the OSD dataset) but differences in the ITS sequences as well as at the genomic level21,54. The distribution of these two cryptic species (BI-genome RCC1105 and BII-genome TOSAG39-1) determined by metagenomic analysis and qPCR suggest that BI could be coastal and extending to polar waters, while BII is adapted to warmer oceanic waters21,22,55,56.

Figure 6
figure 6

Distribution of the major Bathycoccus ASV for OSD2014 (LGC). Legend as in Fig. 3. A zoomed-in map of European waters is provided in Fig. S6.


Two ASVs with more than 200 reads were assigned to the genus Mantoniella, corresponding to a total of 8,570 reads (Table 1). Except for the morphological species M. squamata3,12 and M. antarctica14, no clades based on 18S rRNA gene sequences have been yet described7,16. However, the V4 hypervariable region of the 18S rRNA gene examined using publicly available reference sequences as well as OSD ASVs highlights two new Mantoniella clades, which we named A and B, both with well-supported phylogenies (Fig. 7A) and clear sequence signatures (Fig. 7B).

Figure 7
figure 7

Phylogenetic diversity within the genus Mantoniella. (A) Phylogenetic tree of 19 Mantoniella sequences from the V4 region of the 18S rRNA gene (FastTree). The tree was rooted with the 3 Micromonas sequences (AB183589, HM191693, and JF698749). Legend as in Fig. 2. (B) Alignment of 19 Mantoniella V4 regions, the alignment was 368 bp long, but only the main signatures are shown (between the 20th and 141st position of the original alignment).

The most abundant ASV corresponded to the species M. squamata (4,500 reads) and represented up to 70% of the Mamiellophyceae reads off Greenland (OSD80, Figs 8 and S7), while at all other stations it always accounted for less than 10%. However, this ASV was found at stations with very different environmental conditions, including off Hawaii and in a lagoon on the coast of Uruguay (Fig. 8). This finding is consistent with previous descriptions of M. squamata as a cosmopolitan species3 and several studies reporting in particular its presence in northern high latitudes51,57.

Figure 8
figure 8

Distribution of the major Mantoniella ASVs for OSD2014 (LGC). Legend as in Fig. 3. A zoomed-in map of European waters is provided in Fig. S7.

The ASV corresponding to Mantoniella clade B (4,070 reads) was more widespread, representing more than 1% of the Mamiellophyceae reads at 16 stations (Fig. S1), especially in Venice Lagoon (53% at OSD47, 36% at OSD70 and 12% at OSD69) but also in other moderately warm waters (eastern Mediterranean Sea, Gibraltar, California, Hawaii, Figs 8 and S7), matching GenBank sequences previously found in the Mediterranean Sea8.

No ASV corresponding to Mantoniella clade A was found in the LGC dataset but one ASV from the LW dataset (841 reads) matched this clade. This clade was present only off Greenland (OSD80) which matches the environment where other GenBank sequences from this clade have been obtained (sea ice from the Arctic Ocean58, the White Sea53 and the Baltic Sea59), suggesting that Mantoniella clade A is an ice alga.

Finally, no major ASV corresponding to the species M. antarctica was found in either the LGC or LW dataset. In particular, this species was absent from the single station sampled in Antarctica (OSD187, Palmer Station) in the middle of the austral winter, where only 85 Mamiellophyceae reads were recorded. Similarly, no major ASVs corresponding to the newly described species M. baffinensis and M. beaufortii were found in either the LGC or LW datasets, although a minor ASV corresponding to the latter species was found off Greenland (OSD80)15.

Limitations of the OSD Dataset

The OSD metabarcoding dataset is invaluable to determining the distribution of many phytoplankton groups in coastal waters25,26,60. However, it must be always emphasized that metabarcoding is not a quantitative method because of biases in PCR and because of the variation in the number of 18S rRNA gene copies per organism61. In the case of Mamiellophyceae, because they are small, the number of copies is low61 and does not vary greatly between the different genera (e.g. two and four copies in Bathycoccus and Ostreococcus, respectively62,63). This low variation supports the use of relative number of reads as a semiquantitative proxy of Mamiellophyceae contributions. Another potential problem of the OSD dataset is the fact that sampling was conducted everywhere on almost the same date (in most cases on June 21). Such simultaneous sampling has the advantage of providing a snapshot of the global coastal ocean, which allows analysis of spatial distributions without the impact of seasonality, in contrast to oceanographic expeditions such as Tara Oceans5, which sampled different ecosystems at different times of the year. One limitation of OSD is that the Northern and Southern Hemispheres were sampled at opposite points of the yearly cycle: at the summer and winter solstices, respectively. However, since sampling was mostly conducted in the Northern Hemisphere, this limitation has a low impact on data interpretation. The existence of phytoplankton cycles driven by temporal changes and nutrient cycles in coastal environments64,65,66 may explain why some species were not found in the OSD dataset in regions where strains or clones corresponding to the same species have been isolated before. As an example, Bathycoccus initially isolated from the Gulf of Naples in the Mediterranean Sea20, was not recovered at the Naples OSD station (OSD4), where only 2 Mamiellophyceae reads were obtained. Metabarcoding analyses at the Long Term Ecological Research station in the Gulf of Naples showed that Mamiellophyceae were not found in June67, which may explain why they were absent from the OSD dataset. In contrast, analysis of several time series68 led to the conclusion that M. bravo (previously non Arctic B.E.3 clade) dominated the Micromonas community in summer and should be adapted to warm well-lit coastal waters which is consistent with what we observed in the OSD dataset for which sampling was performed in June.


Determining the biogeographical distribution of phytoplankton species is critical for understanding their ecophysiology in order to determine how they will adapt to predicted climate change and how marine food webs will evolve. Although Mamiellophyceae are clearly the dominant group of green algae in coastal waters25,26, previous analysis could not relate their relative abundance to any environmental variable25. Even analysis at the genus level is not sufficient to detect biogeographical patterns. For example, the genus Micromonas is found at virtually all OSD stations (Fig. 5). The only genus that is not widely distributed is Ostreococcus, which is absent from polar regions. In contrast, analysis at the species/clade levels allows some very clear patterns, in particular with respect to latitudinal distribution (Table 3), to be detected. Some species/clades have quite restricted latitudinal ranges, e.g., M. polaris was found only in Arctic samples, M. pusilla was found only in temperate waters, and Micromonas sp. clade B5 was found only in warm waters. Others are much more widespread, for example, Ostreococcus clade B, which extends from temperate to tropical waters. Some taxa seem to be restricted to specific habitats, in particular, O. mediterraneus is restricted to coastal lagoons. The case of the Mediterranean Sea is also interesting. This sea has been previously shown to harbor specific taxonomic groups such as Chlorodendrophyceae25, clade A6 of Chloropicophyceae26 or the Bolidophyceae Triparma mediterranea69. Here, we found that some temperate species such as M. pusilla or Ostreococcus clade E were absent from this region, but we did not find any species/clade restricted to it.

Table 3 Summary of the coastal distribution of Mamiellophyceae species and clades.

Genetic diversity is quite different between the four genera that we examined. While Bathycoccus is composed of a single clade, at least based on the 18S rRNA gene, Micromonas seems to be extremely diversified with a large number of clades. Although most of the clades found in OSD have been observed before, we uncovered some new diversity. One species, M. bravo, was split into two subclades, namely, B1 and B2, that seem to have distinct distributions. Two new clades were uncovered: Micromonas sp. clade B3, which seems to be restricted to a specific latitudinal band (approximately 45° to 65° N), and Ostreococcus clade E which is very interesting since it is very abundant and has a distinct distribution from the closely related Ostreococcus clade B. Specifically, Ostreococcus clade E is restricted to temperate waters, while clade B is found in tropical waters. Since some oceanic regions are covered by the OSD dataset, it is possible that yet undiscovered Mamiellophyceae clades/species exist, especially in the Southern Hemisphere. To obtain more information on the new clades reported here and to determine whether they correspond to potentially novel species, several strategies are possible. First, now that the geographical distribution of these taxa is being uncovered, we may target specific environments and obtain isolates. Such targeting will allow analysis of finer resolution markers such as the ITS11 and determination of physiological preferences, for example, in terms of temperature70. Another strategy for examining clades that are hard to isolate in culture would be to determine longer sequences of the ribosomal operon, including in particular the ITS region, directly from the environment either by long-amplicon PCR using novel technologies such as nanopore sequencing71 or by extracting them from existing metagenomics datasets such as those obtained during the Tara Oceans project21.

Data Availability

Scripts for mothur and R, and Mamiellophyceae OTU sequences, alignments, assignation and abundance for the LGC and LW datasets are provided as Supplementary Files at ( The R processing script is detailed at


  1. Falkowski, P. G., Schofield, O., Katz, M. E., Van de Schootbrugge, B. & Knoll, A. H. Why is the land green and the ocean red? In Thierstein, H. R. & Young, J. R. (eds.) Coccolithophores: from Molecular processes to global impact, 427–453 (Springer, Berlin, 2004).

  2. Throndsen, J. Occurence and productivity of small marine flagellates. Nor. J. Bot. 23, 269–293 (1976).

    Google Scholar 

  3. Thomsen, H. A. & Buck, K. R. Nanoflagellates of the central California waters: taxonomy, biogeography and abundance of primitive, green flagellates (Pedinophyceae, Prasinophyceae). Deep. Sea Res. Part II: Top. Stud. Oceanogr. 45, 1687–1707, (1998).

    ADS  Article  Google Scholar 

  4. Not, F., Simon, N., Biegala, I. & Vaulot, D. Application of fluorescent in situ hybridization coupled with tyramide signal amplification (FISH-TSA) to assess eukaryotic picoplankton composition. Aquatic Microb. Ecol. 28, 157–166, (2002).

    Article  Google Scholar 

  5. de Vargas, C. et al. Eukaryotic plankton diversity in the sunlit ocean. Science 348, 1261605–1261605, (2015).

    CAS  Article  PubMed  Google Scholar 

  6. Tragin, M., Lopes dos Santos, A., Christen, R. & Vaulot, D. Diversity and ecology of green microalgae in marine systems: an overview based on 18S rRNA gene sequences. Perspectives Phycol. 3, 141–154, (2016).

    Article  Google Scholar 

  7. Marin, B. & Melkonian, M. Molecular phylogeny and classification of the Mamiellophyceae class. nov. (Chlorophyta) based on sequence comparisons of the nuclear- and plastid encoded rRNA operons. Protist 161, 304–336, (2010).

    CAS  Article  PubMed  Google Scholar 

  8. Viprey, M., Guillou, L., Ferréol, M. & Vaulot, D. Wide genetic diversity of picoplanktonic green algae (Chloroplastida) in the Mediterranean Sea uncovered by a phylum-biased PCR approach. Environ. Microbiol. 10, 1804–1822, (2008).

    CAS  Article  PubMed  Google Scholar 

  9. Monier, A., Worden, A. Z. & Richards, T. A. Phylogenetic diversity and biogeography of the Mamiellophyceae lineage of eukaryotic phytoplankton across the oceans. Environ. Microbiol. Reports 8, 461–469, (2016).

    CAS  Article  Google Scholar 

  10. Butcher, R. W. Contributions to our knowledge of the smaller marine algae. J. Mar. Biol. Assoc. United Kingd. 31, 175, (1952).

    Article  Google Scholar 

  11. Simon, N. et al. Revision of the genus Micromonas Manton et Parke (Chlorophyta, Mamiellophyceae), of the species M. pusilla (Butcher) Manton et Parke, of the species M. commoda van Baren, Bachy et Worden and description of two new species, based on the genetic and phenotypic characterization of cultured isolates. Protist 168, 612–635 (2017).

    Article  PubMed  Google Scholar 

  12. Desikachary, T. V. Notes on Volvocales. I. Curr. Sci. 41, 445 (1972).

    Google Scholar 

  13. Manton, I. & Parke, M. Further observations on small green flagellates with special reference to possible relatives of Chromulina pusilla Butcher. J. Mar. Biol. Assoc. U.K. 39, 275–298 (1960).

    Article  Google Scholar 

  14. Marchant, H. J., Buck, K. R., Garrison, D. L. & Thomsen, H. A. Mantoniella in Antarctic waters including the description of M. antarctica sp. nov. (Prasinophyceae). J. Phycol. 25, 167–174, (1989).

    Article  Google Scholar 

  15. Yau, S. et al. Mantoniella beaufortii and Mantoniella baffinensis sp. now. (Mamiellales, Mamiellophyceae), two new green algal species from the high arctic. bioRxiv, (2018).

  16. Guillou, L. et al. Diversity of picoplanktonic prasinophytes assessed by direct nuclear SSU rDNA sequencing of environmental samples and novel isolates retrieved from oceanic and coastal marine ecosystems. Protist 155, 193–214, (2004).

    CAS  Article  PubMed  Google Scholar 

  17. Chrétiennot-Dinet, M.-J. et al. A new marine picoeucaryote: Ostreococcus tauri gen. et sp. nov. (Chlorophyta, Prasinophyceae). Phycologia 34, 285–292, (1995).

    Article  Google Scholar 

  18. Subirana, L. et al. Morphology, genome plasticity, and phylogeny in the genus Ostreococcus reveal a cryptic species, O. mediterraneus sp. nov. (Mamiellales, Mamiellophyceae). Protist 164, 643–659, (2013).

    Article  PubMed  Google Scholar 

  19. Rodríguez, F. et al. Ecotype diversity in the marine picoeukaryote Ostreococcus (Chlorophyta, Prasinophyceae). Environ. Microbiol. 7, 853–859 (2005).

    Article  PubMed  Google Scholar 

  20. Eikrem, W. & Throndsen, J. The ultrastructure of Bathycoccus gen. nov. and B. prasinos sp. nov., a non-motile picoplanktonic alga (Chlorophyta, Prasinophyceae) from the Mediterranean and Atlantic. Phycologia 29, 344–350, (1990).

    Article  Google Scholar 

  21. Vannier, T. et al. Survey of the green picoalga Bathycoccus genomes in the global ocean. Sci. reports 6, 37900, (2016).

    ADS  CAS  Article  Google Scholar 

  22. Limardo, A. J. et al. Quantitative biogeography of picoprasinophytes establishes ecotype distributions and significant contributions to marine phytoplankton. Environ. Microbiol. 19, 3219–3234, (2017).

    CAS  Article  PubMed  Google Scholar 

  23. Kopf, A. et al. The ocean sampling day consortium. Giga Science 4, 27, (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Tragin, M., Zingone, A. & Vaulot, D. Comparison of coastal phytoplankton composition estimated from the V4 and V9 regions of the 18S rRNA gene with a focus on photosynthetic groups and especially Chlorophyta. Environ. Microbiol. 20, 506–520, (2018).

    CAS  Article  PubMed  Google Scholar 

  25. Tragin, M. & Vaulot, D. Green microalgae in marine coastal waters: The Ocean Sampling Day (OSD) dataset. Sci. Reports 8, 14020, (2018).

    ADS  CAS  Article  Google Scholar 

  26. Lopes dos Santos, A. et al. Diversity and oceanic distribution of prasinophytes clade VII, the dominant group of green algae in oceanic waters. The ISME J. 11, 512–528, (2016).

    Article  PubMed  Google Scholar 

  27. Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–41 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. Pruesse, E. et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196, (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. Edgar, R. C., Haas, B. J., Clemente, J. C., Quince, C. & Knight, R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–200 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. Callahan, B. J., McMurdie, P. J. & Holmes, S. P. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. The ISME J. 11, 2639–2643, (2017).

    Article  PubMed  Google Scholar 

  31. Guillou, L. et al. The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 41, 597–604, (2013).

    CAS  Article  Google Scholar 

  32. Katoh, K. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066, (2002).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. Price, M. N., Dehal, P. S. & Arkin, A. P. Fasttree: Computing large minimum evolution trees with profiles instead of a distance matrix. Mol. Biol. Evol. 26, 1641–1650, (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood trees for large alignments. Plos one 5, e9490, (2010).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  35. Kearse, M. et al. Geneious Basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics 28, 1647–9, (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Ronquist, F. et al. MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space. Syst. Biol. 61, 539–542, (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Groisillier, A., Massana, R., Valentin, K., Vaulot, D. & Guillou, L. Genetic diversity and habitats of two enigmatic marine alveolate lineages. Aquatic Microb. Ecol. 42, 277–291, (2006).

    Article  Google Scholar 

  38. Guillou, L. et al. Widespread occurrence and genetic diversity of marine parasitoids belonging to Syndiniales (Alveolata). Environ. Microbiol. 10, 3349–3365, (2008).

    CAS  Article  PubMed  Google Scholar 

  39. Gu, Z., Eils, R. & Schlesner, M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics 32, 2847–2849, (2016).

    CAS  Article  PubMed  Google Scholar 

  40. Demir-Hilton, E. et al. Global distribution patterns of distinct clades of the photosynthetic picoeukaryote Ostreococcus. The ISME J. 5, 1095–1107, (2011).

    CAS  Article  PubMed  Google Scholar 

  41. Clayton, S., Lin, Y.-C., Follows, M. J. & Worden, A. Z. Co-existence of distinct Ostreococcus ecotypes at an oceanic front. Limnol. Oceanogr. 62, 75–88, (2017).

    ADS  Article  Google Scholar 

  42. Bai, M. et al. Molecular Detection and Spatiotemporal Characterization of Labyrinthulomycete Protist Diversity in the Coastal Waters Along the Pearl River Delta. Microb. Ecol. 13–15, (2018).

  43. Li, S., Bronner, G., Lepère, C., Kong, F. & Shi, X. Temporal and spatial variations in the composition of freshwater photosynthetic picoeukaryotes revealed by MiSeq sequencing from flow cytometry sorted samples. Environ. Microbiol. 19, 2286–2300, (2017).

    CAS  Article  PubMed  Google Scholar 

  44. Lin, Y.-C. et al. Community composition of photosynthetic picoeukaryotes in a subtropical coastal ecosystem, with particular emphasis on Micromonas. J. Eukaryot. Microbiol. 64, 349–359, (2017).

    Article  PubMed  Google Scholar 

  45. Acosta, F., Ngugi, D. K. & Stingl, U. Diversity of picoeukaryotes at an oligotrophic site off the Northeastern Red Sea Coast. Aquatic Biosyst. 9(1), 16, (2013).

    Article  Google Scholar 

  46. Wu, W., Huang, B., Liao, Y. & Sun, P. Picoeukaryotic diversity and distribution in the subtropical-tropical South China Sea. FEMS Microbiol. Ecol. 89, 563–579, (2014).

    CAS  Article  PubMed  Google Scholar 

  47. Van Baren, M. J. et al. Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants. BMC Genomics 17, 22, (2016).

    CAS  Article  Google Scholar 

  48. Slapeta, J. et al. Global dispersal and ancient cryptic species in the smallest marine eukaryotes. Mol. Biol. Evol. 23, 23–29, (2006).

    CAS  Article  PubMed  Google Scholar 

  49. Worden, A. Z. et al. Green Evolution and Dynamic Adaptations Revealed by Genomes of the Marine Picoeukaryotes Micromonas. Science 324 (2009).

  50. Lovejoy, C. et al. Distribution, phylogeny, and growth of cold-adapted picoprasinophytes in arctic seas. J. Phycology 43, 78–89, (2007).

    CAS  Article  Google Scholar 

  51. Balzano, S., Marie, D., Gourvil, P. & Vaulot, D. Composition of the summer photosynthetic pico and nanoplankton communities in the Beaufort Sea assessed by T-RFLP and sequences of the 18S rRNA gene from flow cytometry sorted samples. The ISME J. 6, 1480–1498, (2012).

    CAS  Article  PubMed  Google Scholar 

  52. Simmons, M. P. et al. Intron Invasions Trace Algal Speciation and Reveal Nearly Identical Arctic and Antarctic Micromonas Populations. Mol. Biol. Evol. 32, 2219–2235, (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  53. Belevich, T. A. et al. Photosynthetic Picoeukaryotes in the Land-Fast Ice of the White Sea, Russia. Microbial Ecology 1–16, (2017).

  54. Vaulot, D. et al. Metagenomes of the Picoalga Bathycoccus from the Chile coastal upwelling. Plos One 7, e39648, (2012).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  55. Simmons, M. P. et al. Abundance and biogeography of picoprasinophyte ecotypes and other phytoplankton in the Eastern North Pacific Ocean. Appl. Environ. Microbiol. 82, 1693–705, (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Joli, N., Monier, A., Logares, R. & Lovejoy, C. Seasonal patterns in Arctic prasinophytes and inferred ecology of Bathycoccus unveiled in an Arctic winter metagenome. The ISME J. 11, 1372–1385, (2017).

    Article  PubMed  Google Scholar 

  57. Throndsen, J. & Kristiansen, S. Micromonas pusilla (Prasinophyceae) as part of pico- and nanoplankton communities of the Barents Sea. Polar Res. 10, 201–208, (1991).

    Article  Google Scholar 

  58. Bachy, C., López-García, P., Vereshchaka, A. & Moreira, D. Diversity and Vertical Distribution of Microbial Eukaryotes in the Snow, Sea Ice and Seawater Near the North Pole at the End of the Polar Night. Front. Microbiol. 2, 106, (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  59. Majaneva, M., Rintala, J.-M. M., Piisilä, M., Fewer, D. P. & Blomster, J. Comparison of wintertime eukaryotic community from sea ice and open water in the Baltic Sea, based on sequencing of the 18S rRNA gene. Polar Biol. 35, 875–889, (2012).

    Article  Google Scholar 

  60. Kuwata, A. et al. Bolidophyceae, a sister picoplanktonic group of diatoms - a review. Front. Mar. Sci. 5, 370, (2018).

    Article  Google Scholar 

  61. Zhu, F., Massana, R., Not, F., Marie, D. & Vaulot, D. Mapping of picoeucaryotes in marine ecosystems with quantitative PCR of the 18S rRNA gene. FEMS Microbiol. Ecol. 52, 79–92, (2005).

    CAS  Article  PubMed  Google Scholar 

  62. Derelle, E. et al. Genome analysis of the smallest free-living eukaryote Ostreococcus tauri unveils many unique features. Proc. Natl. Acad. Sci. United States Am. 103, 11647–52, (2006).

    ADS  CAS  Article  Google Scholar 

  63. Moreau, H. et al. Gene functionalities and genome structure in Bathycoccus prasinos reflect cellular specializations at the base of the green lineage. Genome Biol. 13, R74 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Cloern, J. E. & Jassby, A. D. Patterns and Scales of Phytoplankton Variability in Estuarine and Coastal Ecosystems. Estuaries Coasts 33, 230–241, (2010).

    CAS  Article  Google Scholar 

  65. Treusch, A. H. et al. Phytoplankton distribution patterns in the northwestern Sargasso Sea revealed by small subunit rRNA genes from plastids. The ISME journal 6, 481–92, (2012).

    CAS  Article  PubMed  Google Scholar 

  66. Lambert, S. et al. Rhythmicity of coastal marine picoeukaryotes, bacteria and archaea despite irregular environmental perturbations. The ISME J. 2019, 388–401, (2019).

    Article  Google Scholar 

  67. Piredda, R. et al. Diversity and temporal patterns of planktonic protist assemblages at a Mediterranean Long Term Ecological Research site. FEMS Microbiol. Ecol. 93, fiw200, (2017).

    CAS  Article  PubMed  Google Scholar 

  68. Foulon, E. et al. Ecological niche partitioning in the picoplanktonic green alga Micromonas pusilla: evidence from environmental surveys using phylogenetic probes. Environ. Microbiol. 10, 2433–2443, (2008).

    CAS  Article  PubMed  Google Scholar 

  69. Ichinomiya, M. et al. Diversity and oceanic distribution of the Parmales (Bolidophyceae), a picoplanktonic group closely related to diatoms. The ISME J. 10, 2419–2434, (2016).

    Article  PubMed  Google Scholar 

  70. Demory, D. et al. Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean. The ISME J., (2018).

  71. Krehenwinkel, H. et al. Nanopore sequencing of long ribosomal DNA amplicons enables portable and simple biodiversity assessments with high phylogenetic resolution across broad taxonomic scale. bioRxiv, (2018).

  72. Worden, A. Picoeukaryote diversity in coastal waters of the Pacific Ocean. Aquatic Microb. Ecol. 43, 165–175, (2006).

    Article  Google Scholar 

Download references


Financial support for this work was provided by the European Union project MicroB3 (UE-contract-287589), the ANR PhytoPol (ANR-15-CE02-0007) and TaxMArc (Research Council of Norway, 268286/E40). M.T. was supported by a PhD fellowship from the Université Pierre et Marie Curie and the Région Bretagne (ARED GreenPhy). We would like to thank the Ocean Sampling Day consortium for providing sequence data and the ABIMS platform in Roscoff for access to bioinformatics resources.

Author information

Authors and Affiliations



D.V. and M.T. conceived the study. D.V. produced some of the figures and edited the paper. M.T. analyzed the data, produced some of the figures and wrote the initial draft of the paper. Both authors reviewed the manuscript.

Corresponding author

Correspondence to Daniel Vaulot.

Ethics declarations

Competing Interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tragin, M., Vaulot, D. Novel diversity within marine Mamiellophyceae (Chlorophyta) unveiled by metabarcoding. Sci Rep 9, 5190 (2019).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing