Identification of a deep-branching lineage of algae using environmental plastid genomes

Domain: biology
Published: 2025-12-14
Editorial outcome: major_revision

Abstract
Marine algae underpin entire ocean ecosystems. Yet algae in culture poorly represent their large environmental diversity, and we have a limited understanding of their convoluted evolution by endosymbiosis. Here, we perform a phylogeny-guided plastid genome-resolved metagenomic survey of Tara Oceans expeditions. We present a curated resource of 660 new non-redundant plastid genomes of environmental marine algae, vastly expanding plastid genome diversity within major algal groups, including many without closely related reference genomes. Notably, we recover four plastid genomes, including one near-complete, forming a deep-branching plastid lineage of nano-size algae that we informally name leptophytes. This group is globally distributed and generally rare, although it can reach relatively high abundance in the Arctic. An near-complete mitochondrial genome showing strong co-occurrence with leptophyte plastids is also recovered and assigned to this group. Leptophytes encompass the enigmatic plastid group DPL2, one of the very few known plastid groups not clearly belonging to major algal groups and previously known only from 16S rDNA sequences. Comparative organellar genomics and phylogenomics indicate that leptophytes are sister to haptophytes, and raise the intriguing possibility that cryptophytes acquired their plastids from haptophytes. Collectively, our study demonstrates that metagenomics can reveal hidden organellar diversity, and improve models of plastid evolution.

Introduction
Eukaryotic algae are essential to the success of life on earth, performing nearly 40% of primary production and forming the basis of many food webs1. Algae are incredibly diverse in forms and functions, ranging from some of the smallest known eukaryotes in the open ocean phytoplankton to undersea forests of giant coastal seaweed. The phylogenetic position of algae in the eukaryotic tree of life shows that they have evolved in multiple supergroups, owing their origins to a complex and largely unresolved history of endosymbioses. The first eukaryotic algae originated from the endosymbiotic integration of cyanobacteria into predatory host cells. This primary endosymbiosis led to the diversification of eukaryotes with photosynthetic organelles called primary plastids in the Archaeplastida supergroup, containing major algal groups such as red algae and green algae (including land plants)2,3. Subsequently, plastids were transferred from red and green algae to unrelated groups of eukaryotes by further endosymbioses, spreading photosynthetic capabilities throughout the tree of eukaryotes4. Major questions related to plastid evolution remain open, notably about the number of endosymbioses and partners involved to explain the observed phylogenetic distribution of plastids. The evolutionary history of complex plastids with red algal origin has been among the most difficult to resolve, in spite of the ecological importance of some of these algae in modern oceans, such as diatoms, dinoflagellates, and coccolithophores5,6. Multiple hypotheses have been proposed, many involving successive endosymbioses between eukaryotes over vast evolutionary distances, but there is no consensus and very little empirical evidence to support one or another hypothesis2,7–9.

A more complete catalogue of plastid genomes across the algal tree is needed to better understand the evolution of plastid endosymbiosis. In recent years, comparatively more data has been produced for nuclear genomes of algae—including many transcriptomes—than for the smaller and in principle easier to sequence plastid genomes10. There are currently several major groups of algae that have poor representation of plastid data. For example, only 17 plastid genomes are available for haptophyte species, one of the most abundant and bloom-forming marine algal groups containing as many as 1000 described species and a much larger environmental diversity5. Beyond known algae, a few so-called deep-branching plastid groups, i.e., plastids that do not belong to any established algal groups, have been reported but currently lack any genomic or morphologic description. The discovery of deep-branching plastid groups is extremely rare, comparable to the discovery of new animal groups11, owing to a good understanding of what the major algal groups are. The most notable cases of new deep-branching groups in the past 20 years include the rappemonads—but they have since been formally assigned to haptophytes into the new class Rappephyceae12—or the enigmatic environmental plastid lineages DPL1 and DPL2 for which only 16S rDNA amplicon sequences are available13. While DPL1 was weakly placed within haptophytes but outside of known classes, DPL2 branched deeper, possibly as sister to haptophytes but without statistical support13. Finally, the Picozoa (previously picobiliophytes), which were originally described as a new algal group with unknown affinities to eukaryotes, are now considered aplastidic members of Archaeplastida14.

Here, we used 280 billion metagenomic reads covering a wide range of Tara Oceans planktonic size fractions15,16 as well as additional resources17,18 to assemble and manually curate 660 non-redundant environmental plastid genomes (ptMAGs). We show that genome-resolved metagenomics is a powerful approach for reconstructing organellar genomes and use this unprecedented plastid genomic resource to determine the phylogeny and geographical distribution of planktonic algae. We report a generally rare but widespread and deep-branching clade of plastid genomes encompassing the enigmatic DPL2 that we informally name leptophytes. From the few Arctic samples where leptophytes were the most abundant, we also recovered a mitochondrial contig that was assigned to this group based on its phylogenetic position and highly significant positive correlation in read coverage. Based on the phylogenetic position of both plastid and mitochondrial genomes, we discuss the implications of leptophytes for our understanding of plastid endosymbioses.

Results
A large resource of environmental plastid genomes from the sunlit ocean
To characterise the diversity of eukaryotic algae in the global sunlit ocean, we surveyed large Tara Oceans metagenomic co-assemblies (~12 million contigs > 2.5 kb) covering plankton size fractions ranging from 0.8 µm to 2 mm (Supplementary Data 1)15,16. These co-assemblies, each deriving from samples from a particular oceanic basin, have been shown to improve the recovery of genomes that are too scarce to be assembled from individual samples16,19. Briefly, we used a phylogeny-guided metagenomic approach based on the RNApolB (rpoB) gene, and complementary genomic and environmental information to characterise and manually curate an initial set of 1,448 plastid metagenome-resolved genomes (ptMAGs) with anvi’o20,21 (see Methods). Two additional single-contig ptMAGs related to the focal clade of our study (see subsequent sections) were subsequently added from mOTUs-db18. After filtering for redundancy (ANI > 98%), our final plastid genome database derived from all oceanic regions consisted of 660 new ptMAGs, as well as 166 reference plastid genomes (Supplementary Fig. 1, Supplementary Data 1). The occurrence of 44 single copy plastid core genes indicated that the ptMAGs are 62.9% complete on average, with low redundancy (average: 2.5%) (Supplementary Fig. 2). 126 ptMAGs contained at least 40 of the 44 core plastid genes and were thus deemed near complete. However, no ptMAG mapped as a circular sequence due to the absence of the ribosomal RNA operon which is often missing from MAGs. The ptMAGs had a median size of 65.7 kbp, with GC content ranging between 24.9% and 46.3%, and encoded up to 168 genes (Supplementary Data 1; Supplementary Figs. 3-5). The ptMAG abundance, as estimated by sequencing depth, varied by more than four orders of magnitude, ranging from a chlorophyte ptMAG with ~21,000× coverage to a diatom ptMAG with only ~2× coverage across all Tara Oceans metagenomes (Supplementary Data 1). Collectively, the ptMAGs were far more abundant in the sunlit oceans compared to selected culture representative genomes (82.5% of the total signal), in line with a previous comparison of nuclear genomes among the same metagenomes16 (Supplementary Fig. 6).

We reconstructed a broad multigene phylogeny of our plastid genome database to assess its taxonomic diversity. Given the large taxon sampling, we inferred a Maximum Likelihood phylogeny using the relatively simple site-homogeneous LG+F+I+G4 model based on 93 plastid-encoded genes. This phylogeny recovered all major groups of algae and is overall in good agreement with previously published plastid trees (Fig. 1, Supplementary Fig. 7)9,22. The ptMAGs occurred in most, but not all, major groups of algae. We did not recover ptMAGs for red algae and glaucophytes, which are known to be rare or absent in the open ocean23, nor for the divergent peridinin plastids of dinoflagellates, which are highly fragmented and lack the rpoB marker gene24. Conversely, the ptMAGs greatly expanded the known plastid genome diversity of ochrophytes (n = 375, including 304 diatoms displaying a very broad cellular size range), and haptophytes (n = 196, including Phaeocystales found in large size fractions likely due to their distinct colony-forming lifestyle5). A smaller number of ptMAGs were also recovered for cryptophytes (n = 16, restricted to the small size fractions), and green algae (n = 45, predominantly found in the smallest size fraction). In multiple cases, the ptMAGs represented deep-branching novel genome diversity within established algal groups where cultured references are lacking. For instance, one ptMAG (REFM_CHLORO_00002) deeply branched as sister to Pavlovales (Fig. 1 and Supplementary Fig. 7). Eight chlorophyte ptMAGs recovered from different oceanic regions formed a monophyletic clade distantly related to a clade of Chloropicophyceae. Within ochrophytes, 15 ptMAGs with a broad geographic distribution were closely related but clearly different from the reference pelagophyte plastid genomes (Supplementary Fig. 8). Finally, among green algae, 13 ptMAGs with a large variation in genome sizes formed a distinct clade related to pedinophyte endosymbionts of dinoflagellates, which include the undescribed MGD and TGD25 as well as Lepidodinium chlorophorum26 (Supplementary Fig. 9). This group might represent a larger diversity of endosymbionts than previously recognised. Taken together, these examples demonstrate the usefulness of metagenomics to recover a broad diversity of plastid genomes among multiple major groups, in particular filling critical evolutionary gaps with environmental genomic diversity for clades lacking reference genomes.

Leptophytes: a new deep branching plastid group
Aside from the extended genomic diversity within clearly defined plastid groups, we also recovered a fully supported deep-branching clade formed by four red algal-derived ptMAGs that is related to, but distinct from all major groups with complex red plastids, i.e., haptophytes, cryptophytes, ochrophytes, and myzozoans (Fig. 1). To facilitate discussion, we propose the informal name leptophytes for this new group of plastid genomes. The name refers to the putative small size (lepto- indicates something small) of the corresponding algal cells, which we infer to be below 5 µm based on genomic size fraction distributions across the Tara Oceans metagenomes (Supplementary Fig. 10). Leptophytes were collectively detected in the surface waters of most oceanic basins (Supplementary Fig. 11). At the level of individual genomes, Lepto-01 and Lepto-02 were only detected in the Arctic Ocean characterised by cooler, less saline, and more nutrient-rich waters, while Lepto-03 and Lepto-04 showed a broader and non-polar distribution associated with warmer, more saline, and nutrient-poor waters (Supplementary Figs. 12-13). Although leptophyte genomes were usually found in relatively low abundance (representing 0.14% of the total plastid signal, and detected in 104 out of 147 Tara stations with a median cumulative coverage of 2.3×), Lepto-01 stood out as one of the most detected plastid genomes in two Arctic stations (up to 124x mean coverage in the 0.8-2000 µm size fraction), providing evidence that leptophytes can experience localised increases in abundance under certain conditions (Supplementary Table 1). Interestingly, two 16S rDNA gene fragments were recovered in Lepto-01 and Lepto-04, respectively, which revealed that leptophytes are most similar to a few amplicon sequences of the enigmatic DPL2 plastid group13. The 16S rDNA of Lepto-04 was 100% similar to DPL2, while Lepto-01 shared 91% similarity to DPL2. The relatedness of DPL2 to leptophytes was confirmed by 16S rDNA phylogeny, which also showed a weak affinity of the group to haptophytes (Supplementary Fig. 14). The reported subtropical distribution and pico-size of DPL213 largely overlap with Lepto-03 and Lepto-04 but not with the Arctic preference of Lepto-01 and Lepto-02, thus altogether indicating that leptophytes form a more diverse and widespread group than the narrower DPL2 lineage.

Lepto-01 is the best representative genome for the group. This assembly had the highest coverage (detected in 20 stations with an average mean coverage of 6.3×) but it was also near complete and contiguous with a single contig of 104,203 bp. This ptMAG contained 144 genes with 118 proteins (no detectable introns) and 24 tRNAs (Supplementary Fig. 15). Interestingly, leptophyte plastid genomes seem to lack inverted repeats commonly found in plastid genomes27, although whether they instead contain direct repeats such as in some haptophytes28, or lack repeat regions altogether remains unresolved (Supplementary Fig. 15). The functional repertoire of Lepto-01 shows that it is a photosynthetic plastid genome, retaining genes for the core components of both photosystem I and II (psa- and psb- genes), carbon fixation (rbcL and rbcS), cytochrome b6/f complex (pet- genes), ATP synthase (atp- genes), and chlorophyll biosynthesis (chlI) (Fig. 2, Supplementary Fig. 15). While less complete and more fragmented, the three other leptophyte ptMAGs are largely syntenic with Lepto-01 and support these functional trends (Supplementary Fig. 16). The near complete assembly of Lepto-01 allowed us to compare its gene content with that of red algae and red algal-derived plastids. UPGMA-clustering of homologous gene occurrence showed that the gene content of leptophytes is most similar to that of haptophytes (Fig. 2). In particular, leptophytes are lacking ten genes (including dnaB, ftsH, petF, psbW, rpl4, rpl18, rpl29, rpl35, sufC, ycf33) that are among the 18 genes almost completely absent in haptophytes, but mostly present in all other algal groups with plastids of red-algal origin (Fig. 2, Supplementary Fig. 17).

Leptophyte plastids have phylogenetic affinities with haptophytes and cryptophytes
To gain further insight into the position of leptophytes in the plastid tree, we constructed and evaluated phylogenies using several complex site-heterogeneous mixture models in Bayesian and ML implementations. These models, which consider site-specific amino-acid frequencies, have been shown to generally improve tree estimations but they come at heavier computational costs29. We thus produced a reduced dataset based on the same 93 genes as in the full phylogeny but containing 107 plastid genomes to speed up the analyses while maintaining the phylogenetic breadth for red algae and red algal plastid-containing lineages. Due to overall higher completeness, reference genomes were preferred over ptMAGs when possible, and the least complete leptophyte ptMAG (Lepto-02) was excluded. The battery of advanced phylogenetic analyses all unambiguously confirmed that leptophytes form a novel group of plastid genomes related to haptophytes and cryptophytes (Fig. 3a). This affinity is also supported by a shared rare bacterial gene replacement by horizontal transfer of the ribosomal protein gene rpl36 into the plastid genomes of all three groups (Fig. 3b). We will refer to this group as the Cryptophytes-Haptophytes-Leptophytes (CHL) group.

Leptophytes were recovered as sister to both haptophytes and cryptophytes (HC-sister topology) with the Bayesian model CAT+GTR+G4 (PP=0.99), as well as the ML models GTR+CAT-PMSF+G4 (BS=88) and LG+MEOW80+G4 (UFB=61) in which site profiles are estimated directly from the data30,31. The same position for leptophytes was recovered with the empirical mixture model cpREV+C60+G4 model and in an analysis that removed the 10 fastest-evolving taxa (Supplementary Figs. 18–19). Because of the relatively modest bootstrap support for the position of leptophytes in ML inferences, we compared the likelihood of the three possible topologies within the CHL group, enforced as topological constraints but letting other branches and parameters to be optimised by ML. Under the GTR+CAT-PMSF model, both alternative topologies were rejected by a likelihood chi-squared test with a Bonferroni correction for multiple comparisons32, and the sister position to cryptophytes was additionally rejected by an AU test (Fig. 3c). The likelihood values under the LG+MEOW80+G4 model had less than four points difference across the three topologies, and none were statistically rejected (Fig. 3c).

We then evaluated whether the position of leptophytes was influenced by two common types of systematic errors in phylogenetic reconstruction: heterotachy of evolutionary rates, and compositional heterogeneity across tree branches. To do this, we calculated the likelihoods of the three alternate phylogenies as fixed topologies under newly developed complex models as additional parameters to the LG+MEOW80+G4 model. Heterotachy was modelled with GHOST33, while compositional heterogeneity was accounted for with the GFmix model31,32. The GHOST model continued to favour the HC-sister topology, but the best topology under the GFmix model changed to support the monophyly of leptophytes and haptophytes (H-sister topology) (Fig. 3a, c). With both models, the alternative tested topologies were rejected by the Bonferroni-corrected likelihood chi-squared test (Fig. 3c). Given the observation that compositional bias may have impacted our phylogenetic reconstructions, we attempted to minimise this artefact by recoding the 20 amino acids to a reduced 4-class alphabet (SR4 recoding)34, and by removing the most heterogeneous sites (~25% of positions in the alignment) with a stationary-based trimmer35. In agreement with the GFmix model, the recoded dataset recovered the H-sister topology, albeit with low support (PP=0.75; Supplementary Fig 20). However, the stationary-trimmed alignment recovered the HC-sister topology, also strong support under the CAT+GTR+G model (PP=0.99, but low support with the LG+MEOW80+G model (UFB=72) (Supplementary Fig. 21). Overall, these results indicate that resolving the topology of the CHL group in general and placement of leptophytes in particular is not trivial, as both HC-sister and H-sister topologies remain credible (Supplementary Note 1).

A mitochondrial genome places leptophytes as sister to haptophytes
Plastid genomes do not necessarily mirror the long-term evolutionary trajectory of their host cell because of the complex history of endosymbioses2,4. In an effort to identify potential nuclear-encoded sequences for leptophytes, we searched the Arctic stations data—where the leptophyte abundance was the highest—for psbO and 18S rDNA candidate genes (see Methods). The psbO gene is essential for photosynthesis, it is always host-encoded and never found in non-photosynthetic organisms36. Although it is derived from the endosymbiont and thus would not be a good phylogenetic marker for the host, our rationale was that it could pinpoint to host contigs that may contain additional genes. These analyses did not provide promising candidates for either gene.

We then turned to mitochondria, as mitochondrial genomes have the double advantage of typically being multi-copy and in theory mirroring the evolution of the host as this organelle traces back to the origin of eukaryotes31,37. From the six Arctic samples where the Lepto-01 ptMAG was the most abundant, we performed a targeted metagenomic co-assembly (total of 2.54 billion metagenomic reads providing a cumulative coverage of 299× for the Lepto-01 ptMAG) that produced 56,103 contigs larger than five kb. Functional annotations based on reference mitochondrial genomes resulted in the identification of 34 mitochondrial contigs (mtMAGs, Supplementary Data 3).

To find a possible correspondence with the Lepto-01 ptMAG, mtMAGs needed to fulfil two complementary requirements. Most importantly, their read coverages should show strong correlation with the Lepto-01 ptMAG across the Tara Oceans metagenomes. Secondly, their phylogenetic position among reference mitochondrial genomes should not be placed within known major algal groups. Among the 34 mtMAGs, one genome (Lepto-01_mtMAG_004) showed highly significant read coverage correlation with the Lepto-01 ptMAG (R2=0.96, p-value < 0.01) (Fig. 4, Supplementary Fig. 22). Most interestingly, Lepto-01_mtMAG_004 also corresponded to a novel deep-branching lineage firmly placed as sister to haptophyte mitochondrial genomes (Fig. 4; UFB=100%, PP=1.0). This mtMAG is 37,793 bp long and contains 37 protein coding genes as well as 22 tRNA genes (Supplementary Fig. 23), with the presence of various marker genes indicating that it is nearly complete. Based on both criteria of abundance and phylogeny, we infer that Lepto-01_mtMAG_004 and the Lepto-01 ptMAG are from the same novel host lineage related to haptophytes.

Methods
Tara Oceans metagenomes
The 937 metagenomes from Tara Oceans used in the study are publicly available at the EBI under project PRJEB402.

Phylogeny-guided genome-resolved metagenomics for plastids
We used two complementary datasets (metagenomic assemblies and evolutionary-informative proteins) to characterise ptMAGs. On the one side, we used 11 large metagenomic co-assemblies from Tara Oceans (~12 million contigs from 798 eukaryote-enriched metagenomes) which were organised into 2550 metabins using constrained automatic binning and processed with anvi’o20,21 v7 for manual binning purposes16. On the other side, we used proteins corresponding to the DNA-dependent RNA polymerase B subunit (RNApolB) and found in those Tara Oceans metabins, in the context of a phylogeny of representative sequences (amino acid level with sequence similarity <90%)47. Until now, the two datasets had only been used to characterise genomes corresponding to RNApolB clades of giant viruses and mirusviruses. Here, we focused on a large plastid RNApolB clade most closely related to that of Cyanobacteria and used this signal as guidance for genome-resolved metagenomics using the anvi’o interactive interface. Briefly, we mainly used sequence composition and differential coverage across metagenomes of the corresponding co-assembly to characterise and manually curate 1448 ptMAGs in the corresponding metabins. The strong correlation between initial signal (number of plastid RNApolB genes) and outcome (number of characterised ptMAGs) across metabins (Supplementary Fig. 1) demonstrated the effectiveness of this method to survey the environmental genomics of plastids in complex marine metagenomes. Preliminary phylogenies (see sections below) with 32 genes indicated a deep-branching lineage (the leptophytes) composed of three ptMAGs.

Recovery of additional ptMAGs from the mOTU database
To broaden the scope of our survey, we exploited 85,123 metagenomic assemblies from the mOTU global metagenomic resource covering a wide range of environmental samples18. A total of 1,969,342 RNApolA genes were previously characterised from this resource48. Note that RNApolA displays a very similar evolutionary signal compared to RNApolB49. Here, we identified 6954 contigs > 50 kbp that contained a RNApolA gene with relatively high sequence similarity to that of our characterised ptMAGs (DIAMOND blast, with percent identify >70% at the amino acid level). Based on preliminary phylogenies, we found one contig characterised from a Tara Oceans metagenome and corresponding to a leptophyte (contig ID Lepto-01_REFM_CHLORO_00001 with a length of 104,203 nt). In addition, we also found one contig (also characterised from a Tara Oceans metagenome) and corresponding to a deep-branching clade of haptophytes (contig ID REFM_CHLORO_00002 with a length of 84,869 nt). We integrated these two contigs into our database of ptMAGs.

Creation of a non-redundant plastid genomic database
We collected all the manually curated Tara Oceans ptMAGs as well as the two ptMAGs from mOTUS-db and included 166 manually selected reference plastid genomes from cultured organisms. We determined the average nucleotide identity (ANI) of each pair of genomes using skani50 v0.2.1. Genomes were considered redundant when their ANI was >98% (minimum alignment of >25% of the smaller genome in each comparison). For genomes found to be redundant, reference chloroplast genomes were selected over ptMAGs, and in most cases where only MAGs were redundant, the longest one was selected. We estimated the completeness and redundancy of each genome based on the occurrence of 44 core-plastid genes51 (Supplementary Table 3), and removed ptMAGs with a redundancy level higher than 15%. This analysis provided a non-redundant database containing the 166 reference plastid genomes and 660 ptMAGs.

To assess potential mitochondrial contamination, all ptMAGs were screened for the presence of 25 canonical mitochondrial genes (Supplementary Table 4), as listed in ref. 52. Five non-redundant ptMAGs were found to contain genes annotated as typical mitochondrial genes, which were confirmed by BLAST searches. Further manual inspection indicated that these instances of contamination were not due to chimeric misassemblies. Instead, they resulted from inadvertent co-binning of mitochondrial and plastid contigs. The contaminated contigs were removed from their respective ptMAGs.

Biogeography of the GOEV database
We performed a mapping of 937 metagenomes from Tara Oceans to calculate the mean coverage (vertical coverage) and detection (horizontal coverage) of each genome in the non-redundant plastid genomic database. Briefly, we used BWA v0.7.15 (minimum identity of 95%) and a FASTA file containing all contigs from the database to recruit short reads from each metagenome53. We considered a genome to be detected in a metagenome when >25% of its length was covered by reads. The number of recruited reads below this cut-off was set to 0 before determining the mean coverage of genomes, as an effort to minimise non-specific read recruitments.

Genome annotation of ptMAGs
Plastid annotation was done with MFannot54 v1.3.6 using the genetic code 11. The resulting ASN format files were converted to GenBank format using the asn2gb utility (https://ftp.ncbi.nlm.nih.gov/asn1-converters/by_program/asn2gb/) from the NCBI toolkit. We then extracted all annotated proteins from the GenBank files using the script gb_to_prot.py (available at https://github.com/burki-lab/ptMAGs/blob/main/src/gb_to_prot.py). For the leptophyte ptMAGs, intron prediction was carried out using RNAweasel (https://megasun.bch.umontreal.ca/apps/rnaweasel/), the 5S rRNA gene was detected with Infernal Cmscan (https://www.ebi.ac.uk/jdispatcher/rna/infernal_cmscan), and maps were generated using OGDraw version 1.3.1 (https://chlorobox.mpimp-golm.mpg.de/OGDraw.html)55. Downstream analyses with OrthoFinder (see Comparative analysis of plastid gene content in leptophytes and related lineages) revealed that MFannot did not detect the rpl22 gene, labelling it as a “hypothetical protein” instead. The annotations of the leptophyte ptMAGs were manually updated to include this gene.

Taxonomic annotation of ptMAGs
We manually determined the taxonomy of ptMAGs based on the global phylogenetic analysis (see section Phylogenomic analyses of plastid dataset), using guidance from the reference plastid genomes.

Phylogenomic plastid dataset assembly
We began by using the two plastid gene sets originally defined by Janouškovec et al 201056: a large set of 68 plastid genes, and a more conserved subset of 34 genes. These served as the foundation for constructing preliminary phylogenies. During dataset assembly (see below), two genes were excluded: acsF due to low taxon occupancy, and psbH due to anomalously long branches in its single-gene tree. This reduced the gene sets to 32 and 66 genes, respectively. The resulting preliminary phylogenies identified leptophytes as a novel clade, but could not confidently resolve their position using maximum-likelihood analyses (Supplementary Figs. 25–26). Therefore, we attempted to increase the phylogenetic signal, by including additional genes used in Ponce-Toledo et al 201757 and Pietluch et al 202446, provided they were also present in leptophytes, resulting in a final set of 93 genes (Supplementary Data 4).

We first built a dataset of 93 protein-coding genes from the 179 reference taxa (166 plastid genomes and 13 cyanobacterial genomes). This was done as follows: (1) Homologous sequences from all reference taxa were retrieved with BLASTP58 v2.15.0 searches using sequences from Fucus vesiculosus (which has a well-annotated plastid genome; NC_016735) as queries (e-value: 1e-02), (2) For each gene, sequences were aligned with MAFFT59 v.7.407 using the --auto option, and then trimmed with trimAL60 v1.4.1 using a gap threshold of 0.8, (3) Single-gene trees were inferred with raxml-ng61 v.1.2.0 using the LG4X model and 100 rapid bootstrap searches, (4) Gene trees were manually parsed to identify duplicates and extremely long branches corresponding to sequences from another gene, which were then removed from the dataset.

We then proceeded to construct a dataset initially including the 1448 ptMAGs identified (including redundant ptMAGs). Using reference sequences from the previous step as queries, we retrieved homologous sequences from the ptMAGs using BLASTP (e-value: 1e-02) and the gene annotation from MFannot. The 93 single-gene dataset was aligned individually using MAFFT-G-INS-I (using the --unalign 0.6 option to avoid over-alignment), and gently trimmed with trimAL (gap threshold: 0.9). Single-gene trees were inferred with IQ-TREE62 v2.2.2.6 using the best fitting model as determined by ModelFinder Plus63. We manually parsed the single gene trees to check for putative chimeras and generated our final dataset comprising 93 genes and 839 taxa (660 ptMAGs and 179 references) with >4% data.

The concatenated alignment was generated as follows: for each curated gene, we first used Prequal64 v1.02 to filter sequence stretches with no clear homology using a posterior probability threshold of 0.95, then aligned with MAFFT-G-INS-I (--unalign 0.6), and subsequently trimmed with BMGE v1.1235 (BLOSUM35 matrix, gap threshold: 0.8). After concatenating, we obtained a supermatrix (839-taxon dataset) with 19,242 aligned amino acid sites, which was used for broad-scale phylogenetic analyses. Finally, we also generated a smaller, 107-taxon dataset to enable analyses under more complex and computationally demanding models. For this dataset, raw sequences for the 93 genes were again filtered, aligned, trimmed and concatenated as previously described, yielding a supermatrix with 20,292 amino acid sites.

Phylogenomic analyses of plastid datasets
Site-homogeneous models. To assess the phylogenetic diversity of the ptMAGs, the full 839-taxon supermatrix was used to compute a maximum-likelihood tree using the best-fitting site-homogeneous model, LG+F+I+G4 in IQ-TREE v.2.2.2.6. Branch support was assessed with 1000 ultrafast bootstrap replicates.

Site-heterogeneous models. We used the smaller, 107-taxon dataset to perform analyses with the more complex, site-heterogeneous models in order to determine the position of leptophytes in the plastid tree. An initial tree was inferred using the best-fitting cpREV+C60+G4 model in IQ-TREE with 1000 ultrafast bootstrap replicates. This phylogeny was used as a guide tree to compute custom site-profiles directly from the input alignment using the programme MEOW31 (-ri-R-C5-fH-l; custom version of MEOW used is provided at https://github.com/burki-lab/ptMAGs/blob/main/src/meow_custom.R), an approach which often outperforms generic mixture models (such as the C-series)65. MEOW (MAMMaL Extension On Whole alignments) extends the MAMMaL approach by using all variable sites in the alignment to estimate custom site-profile classes. Following Williamson et al.31, we estimated three sets of profile classes using varying proportions of high- and low rate classes respectively: (1) MEOW (80, 0) indicates 80 classes from high rate sites and none from low rate sites, (2) MEOW (60, 20) represents 60 classes from high rate sites and 20 classes from low rate sites, and (3) MEOW (40, 40) corresponds to 40 classes each from the two partitions. We inferred a maximum likelihood phylogeny under the best fitting model based on the BIC criterion, LG+MEOW(60, 20)+G4, with 1000 UFBOOT replicates, and for brevity, we refer to this model as LG+MEOW80+G throughout the manuscript.

Another Maximum-likelihood phylogeny was inferred with the 107-taxon dataset with the CAT-PMSF approach30. Briefly, a phylogeny inferred under the site-homogeneous LG+G model in IQ-TREE was used as a fixed tree for analysis with the CAT+GTR+G model in PhyloBayes-MPI66 v1.8. Two Markov Chain Monte Carlo (MCMC) chains were run for more than 5000 cycles until the effective sample sizes of nearly all parameters (seven out of eight) were above 100 (Supplementary Table 5). The posterior mean exchangeabilities and the custom site-frequency profiles were extracted for analysis in IQ-TREE and support was assessed with 100 non-parametric bootstrap replicates.

Finally, we also analysed the 107-taxon dataset in PhyloBayes under the CAT+GTR+G model via three independent MCMC chains. The chains were run for almost 9000 cycles each. After discarding the first 2000 cycles as burn-in, convergence was assessed (with maxdiff reaching 0.047) and consensus trees were generated using the bpcomp command.

Derivatives of 107-taxon dataset. First, we tested the impact of fast-evolving taxa in our dataset by removing 10 taxa (all ochrophytes) with the largest root to tip distances, generating a 97-taxon dataset. Second, we dealt with possible compositional heterogeneity across taxa by using BMGE’s stationary-based trimmer to remove sites based on Stuart’s test of marginal homogeneity (BMGE-sFAST-h0:1-g1; 4752 out of 20,292 sites = 23.4% sites removed). Finally, we dealt with possible compositional heterogeneity and sequence saturation by recoding the dataset into SR4 categories34. Both the non-recoded datasets were analysed in IQ-TREE with the LG+MEOW80+G model with 1000 ultrafast bootstraps. Additionally, the stationary-trimmed alignment was analysed in PhyloBayes using the CAT+GTR+G model, with three MCMC chains runs for 7000 cycles after a burn-in of 5000 cycles, achieving a maxdiff of 0.104. The SR4 recoded dataset was also analysed under the CAT+GTR+G model in PhyloBayes, using three MCMC chains run for 22,000 cycles, with a burn-in of 4000, reaching a maxdiff of 0.101.

Assessing alternative topologies
Site-heterogeneous models. To assess alternate positions of leptophytes, we performed constrained tree searches in IQ-TREE. We considered three possible positions in the algal tree: (1) sister to haptophytes and cryptophytes (HC-sister), (2) sister to haptophytes (H-sister), and (3) sister to cryptophytes (C-sister). For each of these three positions, we considered two topologies; one in which the complex plastids are monophyletic, and the other where the complex plastids are non-monophyletic (as recently recovered by ref. 46), bringing the total number of tested topologies to six. Constrained topologies were inferred with IQ-TREE under the GTR+CAT-PMSF+G and LG+MEOW80+G models for the 107-taxon dataset, and the xmC60SR4 model for the SR4 recoded dataset, with all parameters optimised freely. In the case of the LG+MEOW80+G model, ten independent runs in IQ-TREE were conducted for each constraint to avoid likelihood scores from searches stuck in local optima67. In all cases, the topologies were evaluated with the Approximately Unbiased (AU)68 test implemented in IQ-TREE. Additionally, the best scoring topology under each model was compared with alternative topologies using the Bonferroni-corrected chi-squared test31,32. Briefly, the likelihood ratio test statistic (LRS; two times the difference between the maximised log-likelihood of the two topologies under consideration) is first calculated. The p-value for the chi-squared test (p) is calculated as the probability that a chi-squared random variable would be larger than the LRS with the degrees of freedom defined as the number of branches collapsed in the strict consensus tree of the two trees. The Bonferroni-corrected p-value is calculated as (1-{1-p}A) where A is the set of trees compatible with the strict consensus tree.

GHOST and GF-mix models. We additionally tested the six alternative topologies under GHOST33 and GFmix31,32 as additional parameters to the LG+MEOW80 base model. For GHOST, the log-likelihood scores of the six topologies (inferred under the LG+MEOW80+G model) were calculated under the LG+MEOW80+H8 model in IQ-TREE, using the topologies as fixed trees. The LG+MEOW80+H8 indicates a model with eight linked heterotachy classes and was the best fit model using the BIC criterion when compared to models with four or six heterotachy classes. Topologies were tested using the AU test and the Bonferroni-corrected chi-squared test as described in the previous section.

The GFmix model models compositional heterogeneity by modifying the vector of amino acid frequencies in a branch-specific manner to account for shifts in the relative frequencies of amino acids in different branches of the tree. While prior studies using this model have divided their alignment into multiple partitions to account for varying compositional heterogeneity in mitochondrial and nuclear encoded genes (e.g., refs. 31,32), we opted to use a single partition. This is because we do not expect substantial discrepancy in compositional heterogeneity between the only plastid-encoded genes considered in this study. With no a priori knowledge of how taxa might be compositionally biased, we first estimated the groups of amino acids that are depleted and enriched in different lineages from our data as done in ref. 31. Briefly, we used a custom R script (C. McCarthy, Dalhousie University, Canada, available at https://github.com/burki-lab/ptMAGs/blob/main/src/quickBinomial.R) to carry out the following steps: (1) tabulate the counts of all 20 amino acids for each taxon, (2) perform a chi-squared test on these counts and use the Pearson’s residuals to construct a UPGMA tree of taxa, (3) separate taxa into two groups based on the UPGMA tree, (4) conduct a binomial test for each amino acid and calculate a score reflecting the differences in counts between the two groups, and (5) classify amino acids into “enriched,” “depleted,” or “other” categories based on their scores (Supplementary Note 1). The enriched and depleted classes of amino acids were used by GFmix v1.2 to compute the log-likelihoods of the six alternative topologies, which were inferred using the LG+MEOW80+G model and provided as fixed input trees.

16S rDNA phylogeny
Barrnap v0.9 (https://github.com/tseemann/barrnap) was used to detect 859 bp and 808 bp fragments of the 16S rDNA gene in the Lepto-01 and Lepto-04 ptMAGs respectively. A BLAST search of the Lepto-01 16S rDNA sequence revealed that it was most similar to the DPL213 group with ~91% sequence similarity (accession numbers EF574856 and KX935025). However, the Lepto-04 16S rDNA sequence best BLAST hits included DPL2 as well as cyanobacteria. Manually BLASTing fragments of the Lepto-04 16S rDNA sequence against nt indicated that it was likely chimeric, with the first ~440bp corresponding to DPL2 (100% similarity), and the latter half originating from cyanobacteria. We therefore trimmed the Lepto-04 16S rDNA sequence to only the first 440bp. To confirm the association of leptophytes with DPL2, we constructed a 16S rDNA dataset including Lepto-01, Lepto-04, DPL2, and representatives of each eukaryotic algal clade. The 65-taxon dataset was aligned with MAFFT-L-INS-I, and trimmed with trimAL (-gt 0.1) to get an alignment with 1496 sites. A Maximum-Likelihood phylogeny was inferred with raxml-ng with 20 ML searches and non-parametric bootstrapping until convergence using the GTR+G model.

Rpl36 alignment and phylogeny
To investigate whether leptophytes possessed the rpl36-p type or rpl36-c type gene42, we extracted the L36 amino acid sequences from the 107 taxa in the subset phylogeny when available. The sequences were aligned with MAFFT-L-INS-I, trailing ends trimmed manually, and the alignment was visualised alongside the 93-gene PhyloBayes phylogeny using the R package ggtree69 v3.6.2.

Synteny analysis of leptophyte ptMAGs
Synteny analysis of the leptophyte ptMAGs was performed using the GenBank files generated during genome annotation using PyGenomeViz v1.0.0 via the PyGenomeViz Streamlit Web Application (https://pygenomeviz.streamlit.app/). Sequence similarity of protein coding genes was estimated using MMseqs270 v15-6f452 for reciprocal best-hit CDS search.

Comparative analysis of plastid gene content in leptophytes and related lineages
To gain insights into the evolutionary dynamics and functional capabilities of the leptophyte plastid, we compared its gene content with that of red algae and other red algal-derived plastids. As ptMAGs can have missing genes due to incompleteness, we opted to use only reference plastid genomes where possible. For this analysis, we selected 15 rhodophyte, seven haptophyte, eight cryptophyte and 21 ochrophyte reference plastomes from our plastid genomic database. Similarly, we used the Lepto-01 ptMAG, the only near-complete leptophyte ptMAG, as the sole representative of leptophytes. We extracted amino-acid sequences from all selected plastid genomes and used OrthoFinder71 v2.5.5 with default settings to detect homologous proteins. This analysis yielded 281 phylogenetic hierarchical orthogroups (HOGs) containing 7,648 protein-coding genes (98.5% of the total). However, as no orthology-predictor is perfect, we manually refined the HOGs by inspecting gene annotations, single-gene trees, and performing BLAST and InterProScan searches (Supplementary Data 5). This step yielded 237 HOGs containing sequences from at least three taxa. Heatmaps depicting gene presence/absence were plotted using the R package pheatmap v1.0.12 (https://github.com/raivokolde/pheatmap), and species and orthologs clustered using UPGMA clustering.

Leptophyte associations with environmental parameters
We assessed correlations between leptophyte abundance and eight physiochemical parameters: sea surface temperature, salinity, dissolved silica, nitrate, phosphate, iron, and seasonality indices of nitrate and sea surface temperature. These parameters were obtained from Delmont et al 202216, representing data pulled from climatology and biogeochemical modelling data (World Ocean Atlas 2013 and PISCES v2)72,73 to account for missing physio-chemical samples in the Tara Oceans in-situ dataset. Seasonality indices were defined as the range of the nitrate and temperature in one grid cell divided by the total range of that variable across all Tara sampling stations.

We calculated Pearson’s correlation coefficients between the abundance of each leptophyte ptMAG and the environmental parameters using the R package, corrgram v1.14.

Survey for putative nucleomorphs of leptophytes
We searched for genomic signal corresponding to red-algal nucleomorphs associated with leptophytes across the 11 Tara Oceans metagenomic co-assemblies. Specifically, we surveyed the assembled RNApolB genes, following the protocol used to characterise ptMAGs but this time using publicly available cryptophyte nucleomorph RNApolB genes as a reference. With this approach, we did not identify any nucleomorph-affiliated RNApolB genes co-occurring with the ptMAGs of leptophytes.

Survey for host nuclear sequences of leptophytes
Survey for leptophyte psbO sequences. We considered the psbO gene as a good candidate to attempt finding contigs corresponding to the nuclear genome of leptophytes, as it is encoded by all photosynthetic eukaryotes, usually, in a single copy, in their nuclear genome, and is absent from non-photosynthetic eukaryotes36. We identified psbO sequences in the Arctic metagenomic co-assembly (available at: https://www.genoscope.cns.fr/tara/; where Lepto-01 is abundant) through an HMM search based on the PFAM accession PF01716, carried out using HMMER v3.4 as implemented in anvi’o v8. A total of 51 hits were detected which were added to 346 reference psbO sequences from different algal groups. Sequences were aligned (MAFFT-L-INS-I), trimmed (trimAL, -gt 0.1), and then used to infer a tree with raxml-ng (20 searches, non-parametric bootstrapping until convergence) to determine the phylogenetic affiliation of the 51 psbO sequences. However, all psbO candidates fell within established algal groups, and no putative psbO sequence corresponding to leptophytes could be identified. We hypothesised that this result could be due to low coverage of the leptophyte nuclear genome. We investigated this by focusing on the two filters (both belonging to station 194) where Lepto-01 was among the most abundant eukaryotic plastids (124× and 70× coverage; Supplementary Data 1). We extracted the top 50 most abundant psbO sequences in these two filters from the recently assembled psbO database36. We generated an alignment and inferred a phylogeny as before, but again, did not identify any strong candidates for leptophytes. Most psbO sequences had only a small number of metagenomic reads mapping to them per sample (median number of mapped reads = 3), except for those from highly abundant chlorophytes and ochrophytes. This suggests that nuclear genomes generally have substantially lower coverage than the plastid genomes, making it challenging to retrieve nuclear genomic sequences from eukaryotes other than the most abundant ones.

Survey for leptophyte 18S rDNA sequences. We reasoned that a putative leptophyte 18S rDNA sequence would branch outside known algal lineages, and would correlate in abundance with the ptMAG abundance. We started with a targeted approach by generating a co-assembly of the six samples where Lepto-01 was most abundant using Megahit74 v1.2.9. We then extracted 18S sequences from the co-assembly using Barrnap (length cutoff: 0.2) with the aim of getting a small, manageable pool of candidate sequences for further investigation. These 18S sequences were BLASTed (e-value: 1e-10) against PR275 v5.0.0 and the nt database to identify them, however, all sequences were linked to well established clades and no candidate leptophyte 18S sequence could be identified.

We then turned to metabarcoding data from the top 15 filters where Lepto-01 was most abundant76. We attempted to match the 18S-V9 ASVs (n=5336) to Lepto-01 based on correlation of abundances following the workflow established by Zavadska et al 202477. Briefly, we estimated a correlation coefficient (Spearman’s correlation) between ASV relative abundance and the relative, and absolute abundance of the Lepto-01 ptMAG. We identified 13 and seven candidate ASVs, respectively, that showed a Spearman’s correlation coefficient greater than 0.7. These ASVs were further analysed by performing BLAST searches against the PR2 database and nt database. However, none of the candidates matched leptophytes and the top hits were to cercozoan sequences in each case. This may be due to variation in plastid genome copy number under different conditions, leading to an inconsistent ratio between plastid and nuclear genome abundance.

Survey for leptophyte mitochondrial sequences
Extracting mitochondrial contigs from targeted samples. We first identified core mitochondrial marker genes by functionally annotating a set of seven publicly available haptophyte and cryptist mitochondrial genomes in anvi’o (anvi-run-ncbi-cogs). The following mitogenomes were used: NC_005332.1 (Gephyrocapsa huxleyi), OL703630.1 (Gephyrocapsa oceanica), OL703631.1 (Gephyrocapsa muellerae), AB930144.1 (Chrysochromulina sp. NIES-1333), AF288090.1 (Rhodomonas salina), NC_010637.1 (Hemiselmis andersenii), and NC_031832.1 (Palpitomonas bilix). This step revealed 13 core genes present in these mitochondrial genomes that were functionally annotated as: Cytochrome c oxidase subunit III, Cytochrome c and quinol oxidase polypeptide I, Cytochrome c oxidase subunit II (periplasmic domain), Cytochrome b/b6, Proton-conducting membrane transporter, NADH-ubiquinone/plastoquinone oxidoreductase chain 4L, NADH-ubiquinone/plastoquinone oxidoreductase chain 6, NADH-ubiquinone/plastoquinone oxidoreductase chain 3, ATP synthase subunit ɑ, ATP synthase subunit c, Ribosomal protein L16p/L10e, Ribosomal protein S12/S23, ATP synthase F0 subunit.

We then turned to the co-assembly of the six filters where Lepto-01 was most abundant and extracted all mitochondrial contigs that were at least 5 kbp long. To do so, we first searched for contigs containing the cox3 gene which encodes the cytochrome c oxidase subunit III enzyme, using an HMM search (based on the PFAM accession PF00510) in anvi’o v8, and functionally annotated the contigs as before (anvi-run-ncbi-cogs). We then selected contigs containing at least six of the 13 core genes present in the reference genomes, which yielded a total of 34 contigs representing partial mitochondrial genomes or mtMAGs (Supplementary Data 3).

Abundance correlation analyses. We expected the putative mtMAG of Lepto-01 to show a correlated abundance pattern with the Lepto-01 ptMAG. To test this, we mapped all 34 mtMAGs against 937 metagenomes from Tara Oceans, using the same approach applied to the plastid genomes (see Biogeography of the GOEV database. Abundance between each mtMAG and the Lepto-01 ptMAG was compared and plotted in R using the ggplot278 v3.5.1 and ggpmisc79 0.6.0 packages. Abundance correlations were tested using two ways (1) applying a detection threshold where at least 25% of a genome’s length had to be covered by reads for it to be considered present in a metagenome, and (2) without applying this threshold. Both approaches produced highly consistent results, thus, only results from the analyses without the coverage threshold are presented here.

Phylogenetic inference. We reasoned that a putative leptophyte mitochondrial genome would be expected to form a distinct branch from established clades in a mitochondrial phylogeny. To assemble a mitochondrial phylogenetic dataset, we used the publicly available dataset of Williamson et al 202531 with 93 protein-coding genes and 100 taxa as a starting point. We subset this dataset to retain 50 eukaryotic taxa and the genes present in their corresponding mitochondrial genomes (40 protein-coding genes). To this dataset, we added our 34 mtMAGs and 18 additional reference genomes from various sources to increase the taxon sampling of cryptophytes and haptophytes as well as under-represented lineages such as Picozoa (Supplementary Data 6). This was done as follows: (1) the tool Codetta80 v2.0 was used to determine the genetic code of all mtMAGs and additional reference genomes, (2) mtMAGs and additional reference genomes were annotated MFannot using the standard or mould mitochondrial genetic code as appropriate, (3) The resulting ASN files were converted to GenBank format using the asn2gb tool, and all amino acid sequences were extracted using the custom script gb_to_prot.py (available at https://github.com/burki-lab/ptMAGs/blob/main/src/gb_to_prot.py), (4) Homologous sequences from mtMAGs and additional references were retrieved by BLASTP searches using the 40 genes as queries, (5) Sequences for each gene were aligned using MAFFT-L-INS-I, and trimmed with trimAL using a gap threshold of 0.8, (6) Single-gene-trees were inferred with IQ-TREE using the best-fitting model, (7) Gene trees manually parsed to check for problematic sequences. 12 genes were excluded from the dataset at this point due to low taxon occupancy, and the final dataset comprised 28 protein-coding genes (Supplementary Table 6).

To generate the concatenated alignment, we aligned each gene with MAFFT-G-INS-I (--unalign 0.6), and gently trimmed alignments with BMGE (BLOSUM30 matrix, gap threshold: 0.8). We concatenated the genes to obtain an alignment with 102 taxa, 28 genes, and 6,302 sites. The dataset was used for ML analysis in IQ-TREE using the site-heterogeneous LG+C60+G model with 1000 ultrafast bootstraps. Additionally, we analysed the dataset in a Bayesian framework with PhyloBayes under the CAT+GTR+G model. Three independent MCMC chains were run for 15,000 cycles each, with a burn-in of 4500 cycles, and achieving a maxdiff value of 0.23.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Utilizing the vast data generated by Tara Oceans expeditions, the authors ammassed ~700 non-redundant plastid genomes that are manually curated. They have found plastid genomes from the “Leptophytes”, which is a deep-branching algal lineage. Given their presence in the read data from nano-size fraction, the authors thereby named it as Leptophyte. Thorough phylogenetic analyses revealed that leptophytes forms clade with either haptophytes or cryptophytes, depending on the tree model.\nEven though there are concerns about the novelty and credibility of this study which will be discussed in the following paragraphs, I would like to commend the authors for their efforts in handling and curating such a vast dataset. The scope and aim are clear and straightforward. The findings in this study must provide an important base for exploring the diversity of plastids. However, I’d like to raise two major concerns regarding this study: its originality and the credibility of its taxonomic and evolutionary interpretation.\nFirst, the originality of this study raises concerns regarding its suitability for publication in Nature Communications. This lineage was previously described as DPL2 by Choi et al. (Current Biology, 2017). That study, which was also based on Tara Oceans data, documented the presence of this lineage in the photic zone and within the picoplankton size range. It also proposed a close phylogenetic relationship between DPL2 and haptophytes, with moderate support (posterior probability of 0.92). The current study does not provide significant new biological insights such as morphological or ecological information. Although the plastid genomes of the “Leptophytes” were recovered, their gene content appears largely similar with that of haptophytes (as shown in Figure 2), and no notably unique features are reported.\nWith respect to the taxonomy of this lineage, the authors should conduct a more thorough investigation into its relationship with haptophytes, using not only just DNA sequences in the metagenome data, but also data derived from the actual organisms. Given the phylogenetic placement, relatively short branch lengths, and the high similarity in plastid gene content with haptophytes (Figure 2), it is challenging to rule out the possibility that this group represents just another early-diverging lineage of haptophytes rather than a novel clade. Haptophytes are defined by unique features such as the presence of a haptonema and specific pigment compositions. Without additional morphological data (e.g., FISH to trace the cell), it is premature to propose \"Leptophytes\" as it implies the recognition of a novel (sub-)phylum level eukaryotic lineage different than haptophytes. Such a taxonomic designation would require far more robust and diverse evidence and I think it is currently impossible.\nAlthough this study presents some novel plastid genome assemblies derived from publicly available sequence data, I think the manuscript falls short in terms of originality and lacks sufficient data for the thorough testing of evolutionary and phylogenetic hypotheses expected for publication in Nature Communications.\nLine 205: Please provide a detailed description for the reason why the authors choosed 93 genes. What criteria were applied in choosing these specific genes? I am also curious about whether using an alternative or modified gene set might result in a different topology, or if the current topology is robust and consistent across various gene selections.", "reviewer_2": "The manuscript by Jamy et al. delivers very much awaited results of continued exploration of the Tara Oceans metagenomic data, now focusing on the representation of the diversity of plastid genomes in the data. The scientific merit of the study is obvious. Previous investigations utilizing as phylogenetic markers individual genes retrieved from environmental DNA samples have pointed to the existence of unknown deeply diverged plastid lineages or have documented the existence of novel uncultivated groups forming separate deep lineages within known major algal groups (green algae, ochrophytes, haptophytes), raising the question whether they also have a plastid and if yes, whether it is photosynthetic. The work by Jamy et al. progresses towards addressing these questions, although the concept of the study is admittedly not such as to aspire on provide comprehensive answers. The scope of the study is from the start restricted by focusing on metagenomic data from the sunlit ocean, so it cannot cover organisms that live in other types of marine habitats, let alone those thriving in freshwater ecosystems. Nevertheless, even focusing on one particular category of habitats have yielded important new findings that make the study by Jamy et al. highly valuable. In this regard it is interesting to compare this study with a recently released preprint by Shrestha et al. (bioRxiv", "reviewer_3": "New deep-branching environmental plastid genomes on the algal tree of life\nMahwash Jamy1, Thomas Huber2, Thibault Antoine3, Hans-Joachim Ruscheweyh4, Lucas Paoli5, Eric Pelletier3, Tom O. Delmont3*, Fabien Burki2*\nThe authors have mined Tara Oceans data to assemble and curate MAGs corresponding to plastid genomes, with a focus on those derived by higher-order endosymbioses involving red algal donors. It is a remarkable paper. The authors do not over-state its conclusions. To my knowledge it is indeed the most extensive survey of plastid genomes in this way, and they uncover an incredible wealth of information, including discovery of a new algal lineage, which they reasonably assign the following informal name: leptophytes.\nThe Introduction accurately covers the history of this complex field and is well cited in this regard.\nOne could argue that, in the complete absence of any knowledge of a host for the leptophyte plastid, it is too soon to be proposing evolutionary scenarios about how this organelle came to have a genome that looks like it does. My first reading was exactly this. I was wanting more description of the host lineage search in the main text (not passed on to the Methods, which was done on two occasions). But having read the discussion to the end, I can see why the authors are comfortable floating two hypotheses, both with backbone trees that are clearly labeled as hypothetical. Any way one looks at these data, there are still a lot of gaps to fill in our knowledge; all we know for certain now is that this leptophyte plastid lineage clearly puts it in the haptophyte / cryptophyte part of the plastid tree (based on multiple lines of evidence), but it is nevertheless highly distinct. And so we can reasonably say that whatever the host is, it too is rather distinct from the nuclear component of these algae. And if not, well, that would be really interesting too.\nTo conclude my general comments, this paper has a level of novelty that deserves publication in a high-impact journal – it points to the existence of an entirely new branch of photosynthetic life. That is a rare and exciting find. I have the following specific suggestions for the authors to consider.\nSpecific comments:\n-I suggest the authors add some ‘landmark’ taxa on Fig 1 tree. It is not easy to align the gray ‘reference’ OTUs on Ring 2 with the actual branches (which in most cases are quite far away). So why not provide a few well-known taxon names on the actual branches, e.g, G. huxleyi, Phaeocystis, Thallasiosira, Guillardia, Aureococcus, etc., where there is space. This would help experts pinpoint their favourite groups and see how much new diversity the new paper adds to that particular part of the tree. If done strategically, these additions would not detract from the larger take-home messages.\n-Results – first paragraph. The authors discuss ANI and completeness, which makes sense, but it might be good to also include depth of MAG coverage. This is brought up later when discussing abundance of the leptophytes, but non-specialists (used to sequencing genomes ‘normally’ and not assembling them from metagenomic data) would appreciate getting a sense of the range of depth of sequence coverage in the diversity of ptMAGs.\n-Figure 2. What is the tree topology on the left based on? The legend says a larger version is shown in Supp. Fig 15, but that figure looks to be the exact same as Figure 2 (except for presence of gene names) and doesn’t say what the tree at left is based on either. The legend refers to UPGMA clustering, but which tree, the one on the left or the one on the top? These points need clarification.\nLines 135-137 – “In multiple cases, the ptMAGs represented novel genome diversity…” As written, this statement undersells the significance of the data and is not in line with the novelty conveyed in the abstract. Assuming that the gray reference sequences were chosen to represent the full breadth of sequence diversity from cultured representatives, then I would say that novel genome diversity is massively represented in the tree shown in Figure 1. I guess it depends on what is mean by ‘novel diversity’, but looking within haptophytes, diatoms and pelagophytes, the author’s have recovered a tremendous number of novel genomes. I suggest they highlight this even more in the main text, to be more consistent with the (accurate) description in the abstract.\n-Lines 165-66: “However, efforts to identify potential hosts for Lepto-01 at stations where its signal was strongest were unsuccessful (see Methods).” As noted above, I think the authors would do well to briefly integrate some of this information into the main text. The MS is very short (like an old Letter to Nature) and thus there should be plenty of room. And furthermore, the authors could touch on why it matters what the host is, as a prelude to the Discussion.\n-Line 196: present in all other algal groups shown, or all other algal groups (inc. green and glaucophyte algae)?\n-Line 284: Paralog is not the right word to refer to the c-type rpL36 in the CHL plastid because it doesn’t (obviously) involve gene duplication. Probably xenolog is better (which I don’t see much and am not a fan of). I think the evidence suggests that rpL36 in CH(and now L) is most likely an example of orthologous replacement (i.e., a bacterial ortholog replacing the canonical plastid copy). Whether it is, strictly speaking, an ortholog (i.e., evolved by sequence divergence post speciation) is unclear.\n-Line 337-340. “While we found ample evidence of cryptophyte nucleomorphs elsewhere, we found no evidence of putative leptophyte nucleomorphs”. What does ‘elsewhere’ mean here, exactly? As noted above, I think there would be space to integrate the methods information on how they searched for the leptophyte 18S rRNA gene sequences. This would be good for completeness and would help nonspecialist readers better understand the nuances of the alternative models presented in Fig. k4.\nSigned: John Archibald"}, "author_response": "Dear Editor,\nPlease find below our responses to the comments from the three reviewers on the original manuscript.\nBelow, we have reproduced the decision letter verbatim, with our detailed responses to all comments\ninterleaved in blue for clarity. As you will see, our full answer is rather extensive, but we think that\neven if all our arguments did not (could not) make it to the manuscript, the reviewers would appreciate\na highly detailed letter. Based on the comments, we have extensively modified our manuscript, which\nwe hope will now satisfy the requirements for publication in Nature Communications. We would like\nto thank you and the reviewers for all inputs—we believe that this work has greatly improved in the\nrevision process. Please note that line numbers whenever provided correspond to the manuscript file\nwithout track changes.\nThe most significant change to the manuscript is the retrieval of a mitochondrial MAG inferred to be\nfrom leptophytes, which led to a new main Figure (Figure 4). Thus, we now not only present a near-\nfull plastid genome for a new deep-branching algal group, but also a near-complete mitochondrial\ngenome. This discovery greatly augments our story with new insights into models of plastid evolution.\nThe manuscript title has therefore been updated to: “A new deep-branching environmental lineage of\nalgae”, which better represents the updated manuscript.\nREVIEWER COMMENTS\nReviewer #1 (Remarks to the Author):\nUtilizing the vast data generated by Tara Oceans expeditions, the authors ammassed ~700 non-\nredundant plastid genomes that are manually curated. They have found plastid genomes from the\n“Leptophytes”, which is a deep-branching algal lineage. Given their presence in the read data from\nnano-size fraction, the authors thereby named it as Leptophyte. Thorough phylogenetic analyses\nrevealed that leptophytes forms clade with either haptophytes or cryptophytes, depending on the tree\nmodel.\nEven though there are concerns about the novelty and credibility of this study which will be discussed\nin the following paragraphs, I would like to commend the authors for their efforts in handling and\ncurating such a vast dataset. The scope and aim are clear and straightforward. The findings in this study\nmust provide an important base for exploring the diversity of plastids.\n–Response: We thank the reviewer for their encouraging initial remarks.\nHowever, I’d like to raise two major concerns regarding this study: its originality and the credibility of\nits taxonomic and evolutionary interpretation. First, the originality of this study raises concerns\nregarding its suitability for publication in Nature Communications. This lineage was previously\ndescribed as DPL2 by Choi et al. (Current Biology, 2017). That study, which was also based on Tara\nOceans data, documented the presence of this lineage in the photic zone and within the picoplankton\nsize range. It also proposed a close phylogenetic relationship between DPL2 and haptophytes, with\nmoderate support (posterior probability of 0.92). The current study does not provide significant new\nbiological insights such as morphological or ecological information. Although the plastid genomes of\n1\nthe “Leptophytes” were recovered, their gene content appears largely similar with that of haptophytes\n(as shown in Figure 2), and no notably unique features are reported.\n–Response: We regret that the reviewer does not agree with our opinion—backed up by the other two\nvery positive reviews—that this study presents several major novelties that we believe fully meet the\ncriteria for publication in a top-tier journal like Nat. Comm. Firstly, we would like to insist that this\nstudy goes well beyond the really interesting case of leptophytes. As noted, we present a newly and\nhighly original resource of about 700 manually curated plastid environmental genomes of marine\npelagic algae, including groups such as diatoms or haptophytes that are crucial for ocean ecosystems.\nThis represents the largest database available to date for the broad diversity of plastid genomes,\nincluding many groups that totally lack reference genomes. All of these genomes were made available\nto the scientific community. This dataset provides a better picture than ever before of plastid genomic\ndiversity, and will be inevitable in all future studies aimed at understanding the diversity and evolution\nof marine algae. Moreover, our study is highly novel in that it corresponds to the first global plastid\nmetagenome-assembled genomes dataset–we call them ptMAGs–for environmental algae. Since the\ndeposition of our preprint (on Jan 18 2025), another preprint became available that confirms the high\npotential of this approach for organellar metagenomics (Shrestha et al. 2025. Global metagenomics\nreveals plastid diversity and unexplored algal lineages. https://doi.org/10.1101/2025.03.28.644651.)\nWhile metagenomics has transformed the study of bacteria and archaea, it has been much less applied\nto microbial eukaryotes–owing to their much higher complexity–and only a few small-scale attempts\nhave been made to resolve organellar genomes. Thus, we believe that our global study of marine plastid\ngenomes will serve as a reference for similar studies of environmental organellar genomics in the future.\nOn the perceived lack of novelty compared to the Choi et al. publication (Current Biology, 2017,\nhttps://doi.org/10.1016/j.cub.2016.11.032) initially reporting the DPL2 lineage, we again respectfully\nbut firmly disagree. This initial study was exclusively based on short 16S metabarcoding data, and in\nour view it is not reasonable to downplay the significance of recovering complete genomes—including\nthe full plastid genome of a novel group—as offering limited value compared to a few short 16S\namplicon sequences. As discussed below, we now also present a putative mitochondrial MAG for\nleptophytes, reinforcing the novelty aspect. As the broader field has recognised for a long time for\nprokaryotes, but now also increasingly for eukaryotes (e.g.\nhttps://doi.org/10.1016/j.xgen.2022.100123), genome-resolved metagenomics enables advanced\nphylogenomic analyses with the use of complex models of evolution (which we employ here), gene\ncontent comparisons, and functional inferences that 16S data alone does not provide. Importantly, we\nnot only recover genomes that correspond to the previously identified DPL2 16S lineages, but also\nreveal an unsuspected broader genetic diversity for leptophytes (~10% divergence), which prompted us\nto propose a new group encompassing—i.e. not simply corresponding to—DPL2. We also provide a\nnew important ecological perspective since we show that the group is not always rare, providing a new\nand critical perspective on this lineage.\nWith respect to the taxonomy of this lineage, the authors should conduct a more thorough investigation\ninto its relationship with haptophytes, using not only just DNA sequences in the metagenome data, but\nalso data derived from the actual organisms. Given the phylogenetic placement, relatively short branch\nlengths, and the high similarity in plastid gene content with haptophytes (Figure 2), it is challenging to\nrule out the possibility that this group represents just another early-diverging lineage of haptophytes\nrather than a novel clade. Haptophytes are defined by unique features such as the presence of a\n2\nhaptonema and specific pigment compositions. Without additional morphological data (e.g., FISH to\ntrace the cell), it is premature to propose \"Leptophytes\" as it implies the recognition of a novel (sub-\n)phylum level eukaryotic lineage different than haptophytes. Such a taxonomic designation would\nrequire far more robust and diverse evidence and I think it is currently impossible.\n–Response: We agree with the reviewer that isolating the host cell of leptophytes is of utmost\nimportance, and we have already stated this in the discussion (lines: 391-393). Of course, were we able\nat this point to obtain morphological information on the host cells, we would include that in the\nmanuscript. Unfortunately, this is an unrealistic request for a manuscript revision. As we show\n(Supplementary Figure 12), leptophytes are often extremely rare, and the few places where they are\nrelatively less rare are very hard to reach (for example in the Canadian arctic). Even if we had suitable\nsamples available with confirmed presence of leptophytes at high enough abundance—which we don’t,\nestablishing a FISH assay as suggested takes several months of optimisation in the best case scenario.\nTo put this in perspective, the Burki lab has recently hired a postdoc to carry out just that–finding the\nleptophyte cells–but this is planned over a 3 years period.\nRegarding naming the new lineage leptophytes, we argue that it is now widely accepted across the\ndomains of life—Bacteria, Archaea, viruses, but also eukaryotes—that even single-gene sequence data\nalone can justify the informal naming of new lineages. Of course genomic data is preferrable; the\nfamous case of Asgard Archaea is one recent example where metagenomics led the to the informal\ndescription of an entire superphylum (https://doi.org/10.1038/nature21031,\nhttps://doi.org/10.1371/journal.pgen.1007080). For eukaryotes, one can think of MALV or MAST as\nimportant lineages that were initially exclusively named based on single-gene sequence data, but there\nare many other examples. With leptophytes, we emphasize that we are not proposing a formal\ntaxonomic classification here, but simply acknowledging—based on plastid genome data, including a\nnear-complete genome—a new distinct environmental clade, and giving it an informal name to facilitate\ndiscussion. While our plastid data remain ambiguous regarding the exact position of leptophytes, our\nnew mitochondrial data is clearer: leptophytes are sister to haptophytes. Whether this means that in the\nfuture haptophytes will be expanded to include leptophytes, or that leptophytes will remain a distinct\nlineage, one currently cannot say as it will require detailed morphological data not available at the\nmoment (for example to check for the presence of a haptonema, as suggested by the reviewer). We have\nnow made this clearer in the discussion (lines: 391-393).\nBut, even if future work shows that these organisms fall within haptophytes, we believe that the name\n“leptophytes” would still appropriately apply to this specific lineage. Among the many examples that\nwe could cite to support our view, one relatively recent discovery (or re-discovery) is particularly\nrelevant to the discussion here as it also involves haptophytes. Rappemonads were initially named to\ndescribe a group of plastid 16S rRNA sequences of uncertain evolutionary origin, but weakly associated\nwith haptophytes (http://doi.org/10.1128/AEM.64.1.294-303.1998,\nhttps://doi.org/10.1073/pnas.101333710). As a putative new algal lineage, this group of amplicon\nsequences was informally named rappemonads (some low resolution CARD-FISH images confirmed\nthe presence of plastids, but otherwise did not provide any morphological clues as to what this group\nwas). Years later, it took the lucky establishment of a culture (Pavlomulina ranunculiformis) that turned\nout to be closely related to the environmental sequences of rappemonads to enable more detailed\nmorphological work and sequencing data to unambiguously show that Pavlomulina and more generally\nthe rappemonads are in fact bona fide members of haptophytes, forming a new class within the group\nwhich was called Rappephyceae (http://doi.org/10.1016/j.cub.2021.03.012). Thus, as this example\nshows, the informal naming of rappemonads based on sequence data did not preclude the later\nestablishment of a high-ranked taxonomic group of haptophytes based on a culture, on the contrary it\ninspired its name. We believe that the very same situation applies to leptophytes, with the important\ndifferences that we already have plastid genomes not just 16S rDNA, now likely also a near-complete\nmitochondrial contig, and we know the group is “at best” sister to haptophytes, not within it.\nAlthough this study presents some novel plastid genome assemblies derived from publicly available\nsequence data, I think the manuscript falls short in terms of originality and lacks sufficient data for the\nthorough testing of evolutionary and phylogenetic hypotheses expected for publication in Nature\nCommunications.\n–Response:\nAt the risk of repeating ourselves, we respectfully disagree in full with the notion that we just present\n“some novel plastid genomes”. As argued above, we strongly believe that our study is much, much\nmore than that and continue to think (as reviewers 2 and 3 do), even more than before based on the\nadded analyses, that its scope is well within the range of Nat. Comm.\nLine 205: Please provide a detailed description for the reason why the authors choosed 93 genes. What\ncriteria were applied in choosing these specific genes? I am also curious about whether using an\nalternative or modified gene set might result in a different topology, or if the current topology is robust\nand consistent across various gene selections.\n–Response: Thank you for pointing this out. This was lacking and we have now included a detailed\ndescription of the genes selected in the Methods section (lines 512-522):\n“We began by using the two plastid gene sets originally defined by Janouškovec et al 201056: a larger\nset of 68 plastid genes, and a more conserved subset of 34 genes. These served as the foundation for\nconstructing preliminary phylogenies. During dataset assembly (see below), two genes were excluded:\nacsF due to low taxon occupancy, and psbH due to anomalously long branches in its single-gene tree.\nThis reduced the gene sets to 32 and 66 genes, respectively. The resulting preliminary phylogenies\nidentified leptophytes as a novel clade, but could not confidently resolve their position using maximum-\nlikelihood analyses (Supplementary Figs. 24-25). Therefore, we attempted to increase the phylogenetic\nsignal by including additional genes used in Ponce-Toledo et al 201757 and Pietluch et al 202446,\nprovided they were also present in leptophytes, resulting in a final set of 93 genes (Supplementary Table\n6).”\nSupplementary Table 6 lists the genes included in our analyses as well as the corresponding source\nstudies. We emphasize that our study represents the most comprehensive plastid phylogenomic analyses\nto date with a substantially expanded dataset. Notably, we employed highly sophisticated models\nincluding the recently developed site- and branch-heterogenous substitution models presented in\nWilliamson et al 2025 (https://doi.org/10.1038/s41586-025-08709-5).\nThe phylogenies inferred with the 32 and 64 gene-set concatenated alignments are consistent with the\nphylogeny inferred with the final 93 gene dataset, with branch support largely increasing the more genes\nare included. Leptophytes branch sister to both cryptophytes and haptophytes in all phylogenies\n(CAT+GTR+G model), albeit with low support. Overall, these results indicate that the topology\nobtained is robust across various gene selections, but varies with the model used (e.g. the site-\nheterogenous CAT-GTR+G model vs. the site-and-branch-heterogeneous GF-MIX model) as described\nin the main text.\nReviewer #2 (Remarks to the Author):\nThe manuscript by Jamy et al. delivers very much awaited results of continued exploration of the Tara\nOceans metagenomic data, now focusing on the representation of the diversity of plastid genomes in\nthe data. The scientific merit of the study is obvious. Previous investigations utilizing as phylogenetic\nmarkers individual genes retrieved from environmental DNA samples have pointed to the existence of\nunknown deeply diverged plastid lineages or have documented the existence of novel uncultivated\ngroups forming separate deep lineages within known major algal groups (green algae, ochrophytes,\nhaptophytes), raising the question whether they also have a plastid and if yes, whether it is\nphotosynthetic. The work by Jamy et al. progresses towards addressing these questions, although the\nconcept of the study is admittedly not such as to aspire on provide comprehensive answers. The scope\nof the study is from the start restricted by focusing on metagenomic data from the sunlit ocean, so it\ncannot cover organisms that live in other types of marine habitats, let alone those thriving in freshwater\necosystems. Nevertheless, even focusing on one particular category of habitats have yielded important\nnew findings that make the study by Jamy et al. highly valuable. In this regard it is interesting to\ncompare this study with a recently released preprint by Shrestha et al. (bioRxiv,\nhttps://doi.org/10.1101/2025.03.28.644651), which reports on an exploration of plastid genomes in a\nmuch broader set of metagenomic samples (including the freshwater ones). The general conclusions\nof both independent studies are largely overlapping, including the possibly most exciting result of both\nstudies, that is obtaining the first (nearly complete) plastome sequences from an uncultivated marine\nlineage denoted by Jamy et al. as “leptophytes” and embracing the previously known DPL2 lineage of\nplastidial 16S rRNA genes hypothesized to represent a new algal group. Thanks to the effort by both\nteams it is now clear there indeed exists a deeply diverged evolutionary lineage of plastids affiliated to\nthe plastids from haptophytes and cryptophytes. Nevertheless, the identity of the actual\norganismal (i.e., host) lineage harbouring these plastids remains unknown, leaving a major gap in our knowledge of\nalgal diversity open.\nThus, while I am generally very positive about the study by Jamy et al. and I believe it is in principle\nworth publishing in a top-tier journal like Nature Communications, I believe some extra work and\nimprovements in the presentation of the data is necessary to more fully realize the potential of the\nmaterial in hand. Below I provide a list of points that the authors should address. Despite their number\nthey do not require an excessive amount of time or effort, and I hope they are all constructive, helping\nto make the paper even better than it is now.\n–Response: We sincerely thank the reviewer for their encouraging remarks, and thoughtful,\nconstructive, extensive, and detailed review. We have addressed their suggestions below, some of which\nhave greatly improved the manuscript to make it, we believe, more impactful.\n- line 94: two references are cited #16 and #19. The latter is a paper describing the development of a\nparticular software (MarkerMAG) and it is not clear to me how this paper relates to what the authors\nmention in the respective sentence citing the paper. Is it possible that you wanted to cite something else\nhere? Regardless, if the tool MarkerMAG was indeed used in the study, it should be clear how (it is not\nmentioned in the Methods section).\n–Response: We thank the reviewer for identifying this error, as the ref #19 was inadvertently inserted\nin the sentence without any relevance. We have now replaced the reference by the relevant one.\n- The description of methods and procedures additionally misses a description of how the mOTUs-db\nwas used to retrieve the two ptMAGs analysed by the authors. I have checked the mOTUs-db website\nit is not at all obvious how to proceed to retrieve any ptMAG from the database, so please add a few\nlines on this.\n–Response: The reviewer is correct about the methods section not extensively describing the recovery\nof two relevant ptMAGs from mOTUs. To address this point, we have now added this paragraph in the\nmethod section (lines 454-465):\n“Recovery of additional ptMAGs from the mOTU database.\nTo broaden the scope of our survey, we exploited 85,123 metagenomic assemblies from the mOTU\nglobal metagenomic resource covering a wide range of environmental samples18. A total of 1,969,342\nRNApolA genes were previously characterized from this resource 48. Note that RNApolA displays a\nvery similar evolutionary signal compared to RNApolB 49. Here, we identified 6,954 contigs >50 kbp\nthat contained a RNApolA gene with relatively high sequence similarity to that of our characterized\nptMAGs (DIAMOND blast, with percent identity >70% at the amino acid level). Based on preliminary\nphylogenies, we found one contig characterized from a Tara Oceans metagenome and corresponding to\na leptophyte (contig ID Lepto-01_REFM_CHLORO_00001 with a length of 104,203 nt). In addition,\nwe also found one contig (also characterized from a Tara Oceans metagenome) and corresponding to a\ndeep-branching clade of haptophytes (contig ID REFM_CHLORO_00002 with a length of 84,869 nt).\nWe integrated these two contigs into our database of ptMAGs.”\n- line 101: “filtering for redundancy (average nucleotide identity <98%)” – the sentence does not make\nsense to me unless assuming that instead of “<98%” there should be “>98%” used in the text.\nPlease check this.\n–Response: Thank you, fixed!\n- There seems to be some chaos regarding the number of reference plastid genomes used in the analyses\nby the authors. According to the information provided in line 102 and then later in the Methods section\n(lines 381 and 389), the authors selected 164 reference plastid genomes. These are supposed to be listed\nin Supplementary Table 1 (see line 103) and I assume these correspond to plastomes with identifiers\nstarting with “REFG_”. However, there are 167 rather than 164 REFG_” genomes listed in the table.\nFurthermore, while there are 167 genomes listed, the identifiers go from REFG_CHLORO_00001 to\nREFG_CHLORO_00166. This is because the table includes two different plastomes labelled as\n“REFG_CHLORO_00165”, one corresponding to KY860574 (a cryptophyte plastome) and included\nin the list between REFG_CHLORO_00020 and REFG_CHLORO_00021, and the other\ncorresponding to NC_020371 and listed at the expected position (after REFG_CHLORO_00164). I am\nnot sure if such a labelling discrepancy might have affected the analyses reported by the authors, but\nthey certainly have to check this carefully and also ensure each plastome has a unique identified in the\ntable. To make the confusion even worse, at other places in the manuscript (legend to Fig. 1, line 117;\nMethods – line 419 and 435) the authors mention the use of 180 reference plastid genomes. If two\ndifferent sets of reference plastid genomes were indeed used in different analysis (but I guess this is\npossibly not true), then some clarification for the rationale is needed and a list of all the 180 references\nneeds to be provided. Finally, still another number of reference plastid genomes – 166 – is mentioned\nin the legends to Supplementary Figs 2-5.\n–Response: Thank you very much for pointing this out. We greatly apologise for the confusion and\nhave now fixed the inconsistencies. We carefully checked our collection of ptMAGs and reference\ngenomes and report the correct numbers below as well as in the manuscript:\n● 660 ptMAGs. This is down from 667 ptMAGs in the previous version, following the removal\nof seven ptMAGs with high redundancy levels (>15%). Additionally, these 660 ptMAGs are,\nto the best of our knowledge, now free from mitochondrial contamination (see response to the\ncorresponding comment below). The seven ptMAGs removed are:\nTARA_CHLORO_00225, TARA_CHLORO_00009, TARA_CHLORO_00548,\nTARA_CHLORO_00377, TARA_CHLORO_00247, TARA_CHLORO_00285, and\nTARA_CHLORO_00493.\n● 166 reference plastid genomes. This is down from 167 references in the previous version,\nfollowing the removal of a taxonomically redundant reference (“Pavlova sp NIVA-4/92” as\nnoted by the reviewer in another comment). These reference plastid genomes were used for\nboth the phylogenetic analyses (Fig. 1, with a subset of taxa in Fig. 3), as well as for\ncomparisons with the ptMAGs (Supplementary Figs. 2-6, with a subset of taxa in Fig. 2).\n● In addition, we used 13 reference cyanobacteria as outgroups in the phylogeny in Fig. 1 and\nSupplementary Fig. 7. The total number of references in Fig. 1 is therefore 179.\nAccordingly, we have:\n● Updated the numbers in the manuscript. Deviations from these numbers are more clearly\nexplained where applicable. For example, Paulinella was not included in the comparisons in\nSupplementary Figs. 2-6, thus the number of reference plastid genomes mentioned in the\ncorresponding legends is 165.\n● Re-run the alignments and phylogeny for Fig 1.\n● Re-run the analyses for Supplementary Figs 2-6.\n● Updated Supplementary Table 1.\n● Updated the data provided in the Figshare repository.\n- I think a major omission in the description of the methodology employed by the authors concerns the\nprocedure used to create Fig. 2 (and its more detailed version displayed as Supplementary Fig. 15). The\nauthors mention the analysis is based on 355 “plastid-encoded genes” (is a gene really “encoded”?),\nbut it is not specified how these genes were selected and, most crucially, how the presence/absence of\nparticular genes has been examined in individual genomes. Some plastid genes are rapidly evolving\nand it may be challenging to identify orthologs correctly. Furthermore, as is apparent from\nSupplementary Fig. 15 many of the 355 genes are labelled orfXXX (where XXX stands for a particular\nnumber), i.e. they do not correspond to broadly conserved and well-annotated plastid genes. Please,\nprovide a description how these genes were delimited and how orthology across the plastid genomes\nanalysed was assessed. We need to be certain the presence/absence pattern of these genes as displayed\nin the scheme does not reflect simply the occurrence of the same “orfXXX” annotated as such by\nMFannot in different plastid genomes – note that the same label frequently means only the same length\nof the orfs, i.e. the same number of codons, not orthology as such. I think that for the sake of\nreproducibility, the authors should provide a table listing all the genes for all the plastomes so that an\ninterested reader could unambiguously identify each gene (at the sequence level); these data are not\nprovided even at the Figshare site linked to the manuscript.\n–Response: We thank the reviewer for this comment as we were unaware that orfXXX indicates only\nthe number of codons. Our previous analysis assumed orthology based only on gene annotation by\nMFannot.\nWe have now redone the analysis and described the methods in the manuscript (lines 681-696):\n“Comparative analysis of plastid gene content in leptophytes and related lineages\nTo gain insights into the evolutionary dynamics and functional capabilities of the leptophyte plastid, we\ncompared its gene content with that of red algae and other red algal-derived plastids. As ptMAGs can\nhave missing genes due to incompleteness, we opted to use only reference plastid genomes where\npossible. For this analysis, we selected 15 rhodophyte, seven haptophyte, eight cryptophyte and 21\nochrophyte reference plastomes from our plastid genomic database. Similarly, we used the Lepto-01\nptMAG, the only near-complete leptophyte ptMAG, as the sole representative of leptophytes. We\nextracted amino-acid sequences from all selected plastid genomes and used OrthoFinder71 v2.5.5 with\ndefault settings to detect homologous proteins. This analysis yielded 281 phylogenetic hierarchical\northogroups (HOGs) containing 7,648 protein-coding genes (98.5% of the total). However, as no\northology-predictor is perfect, we manually refined the HOGs by inspecting gene annotations,\nsingle-\ngene trees, and performing BLAST and InterProScan searches (Supplementary Table 10). This step\nyielded 237 HOGs containing sequences from at least three taxa. Heatmaps depicting gene\npresence/absence were plotted using the R package pheatmap v1.0.12\n(https://github.com/raivokolde/pheatmap), and species and orthologs clustered using UPGMA\nclustering. ”\nThe results of this new analysis are consistent with previous results, and show that leptophyte plastids\nmost closely resemble haptophyte plastids. The new Supplementary Table 10 now also allows readers\nto identify the sequences in each orthologous group from every plastid genome used in our analysis.\n- The authors assessed the completeness of their ptMAGs by checking the occurrence of 44 core-plastid\ngenes listed in Supplementary Table 5. A large proportion of these genes encode components of the\nphotosynthetic apparatus, so these are expected to be missing from plastomes coming from non-\nphotosynthetic plastids. It is not clear to me whether the authors have used the completeness as a\ncriterion for filtering out any of the potential ptMAGs and if yes, whether this might systematically\nremove from their final ptMAG set the plastomes of non-photosynthetic plastids. Regardless, are there\nany ptMAGs in the final dataset that are likely representing non-photosynthetic taxa? I believe this is\nrelevant question and an interesting aspect of plastid diversity ignored in the present version of the\nmanuscript.\n–Response: While we estimated completeness of the ptMAGs during our investigations, we did not\nexclude any based on this criterion alone, as most of them had a relatively high completeness (average\ncompletion of 63%). Our criteria to remove ptMAGs were their length (minimum 20 kb), and\nredundancy estimate (max of 15%). As a result, our workflow is compatible with the recovery of non-\nphotosynthetic ptMAGs, especially given that the marker gene used to extract ptMAGs (RNApolB) is\nnot related to photosynthesis. Based on functional annotations in the context of the main phylogeny\n(Figure 1), we did not identify any clade of non-photosynthetic ptMAGs in our database. As stated in\nthe manuscript, we are aware that our workflow could not retrieve the peridinin plastid genomes of\ndinoflagellates (both photosynthetic and non-photosynthetic), given their highly unusual structure\n(highly fragmented and lacking rpoB).\nAnalyses specifically concerning leptophytes:\n- Plastid genomes typically include a duplicated region known as the inverted repeat, but surprisingly\nthis term does not appear at all in the text despite the fact it is an important feature with direct bearings\nto the process of assembly of plastome sequences. It is particularly notable that the leptophyte ptMAG,\nalthough incomplete, implies a plastome organization lacking an inverted repeat (at least judging from\nSupplementary Fig. 13). I believe the authors should explicitly mention whether they see any evidence\nfor inverted repeats being part of leptophyte plastomes (careful manual analysis of the assembly data\nincluding raw reads may be necessary to clarify this), and if not, how unusual this would be compared\nto plastomes of haptophytes and cryptophytes. In addition, I think the authors should explicitly\ncomment on what the Lepto-01 ptMAG is most likely missing. Judging from the map it is possible that\nonly the remaining parts of the 16S and 23S rRNA genes (rns and rnl) plus two tRNA genes (trnI and\ntrnA) that are usually placed in between these two genes are missing. In fact, the annotation of the\nLepto-01 ptMAG as presented by the authors in Supplementary Figs 13 and 14 (and the respective\nannotation file at the linked Figshare site) is incomplete and misses a 5S rRNA gene (rrn5) that is\nlocated exactly when one would expect in analogy with other plastomes – in the unannotated (“intergenic”)\nregion just downstream the rnl gene; the presence of the gene is readily seen when the respective region is analysed using Infernal Cmscan\n(https://www.ebi.ac.uk/jdispatcher/rna/infernal_cmscan). Hence, the authors should update the\nannotation of the ptMAG by adding this extra gene.\n–Response:\nRegarding inverted repeats\nSince many plastid genomes often have inverted repeat (IR) regions, we did consider IR regions during\nour original analysis of the leptophyte plastid genomes. We did not observe an IR region, and originally\nthought that this could either reflect a true absence of IR regions, or simply be an artefact of sequence\nassembly (resolving repeats in metagenome assemblies of short-read sequence data is notoriously\nchallenging).\nUpon further consideration of the reviewer’s comment, we realised that the Lepto-01 contig—flanked\nby 16S rDNA on one end and 5S and 23S rDNA on the other—indeed implies the lack of IR regions.\nThe question of whether the leptophyte plastid genome lacks repeat regions altogether (e.g. as in\nPavlovales and certain rhodophytes), or whether it has direct repeats instead (e.g. as in\nIsochrysidales\nand certain land plants) is difficult to resolve. In principle, one could infer the presence/absence of\ndirect\nrepeats (DR) by examining read depth across the plastid genome; if present, the repeat regions would\nbe expected to have approximately twice the coverage compared to the rest of the genome. In practice,\nhowever, this approach is difficult to apply in this specific case. The Lepto-01 ptMAG contains only a\nsmall fragment of the putative DR region (if it exists), i.e. the 16S and 23S rRNA gene fragments. These\ngenes contain highly conserved sequence regions and it is difficult to distinguish between related taxa\nusing the corresponding raw reads. This is one reason why rDNA genes are frequently missing from\nMAGs, or are chimeric. In fact, this may explain the likely 16S rRNA chimera we observe in the Lepto-\n04 ptMAG. Overall, we do not believe it is currently possible to resolve the presence or absence of DR\nregions in the leptophyte plastid genomes given the available data. Addressing this question will require\neither isolating leptophyte cells, or long-read metagenomics.\nWe have now added the following sentence to the main text (line 197-199): “Interestingly, leptophyte\nplastids genomes seem to lack inverted repeats commonly found in plastid genomes27, although whether\nthey instead contain direct repeats such as in some haptophytes28, or lack repeat regions altogether\nremains unresolved (Supplementary Fig. 14).”.\nWe have also added a panel to Supplementary Fig. 14 (see below), with cartoons of possible leptophyte\nplastome organisation.\nRegarding missing genes\nFirst, we thank the reviewer for pointing out the missing 5S rRNA gene. The annotation for the Lepto-\n01 ptMAG has now been updated to include this gene in the genome map (Supplementary Fig. 14) and\nall relevant files shared on Figshare. On a related note, during the gene content analysis with\nOrthoFinder, we noticed that MFannot fails to correctly identify the rpl22 gene in any input genome.\nIn the Lepto-01 ptMAG, the gene was identified as orf120. The annotation of this gene has now also\nbeen updated.\nFurthermore, we now explicitly discuss other leptophyte missing genes in Supplementary Fig. 14. In\nthe case that there are no repeat regions, it is possible that the only missing genes are trnI and trnA.\nIf\nthe plastid genomes contain direct repeats, leptophytes could be missing additional protein-coding\ngenes present in the small single-copy (SSC) region.\n- The authors have attempted to illuminate the nature of the “host” lineage harbouring the leptophye\nplastid. Specifically, in Results they write (lines 165-166): “However, efforts to identify potential hosts\nfor Lepto-01 at stations where its signal was strongest were unsuccessful (see Methods)”. In Discussion\nthey then add this (lines 335-340): “While we found ample evidence of cryptophyte nucleomorphs\nelsewhere, we found no evidence of putative leptophyte nucleomorphs (see Methods)”. The methods\nsection then indeed includes a section describing specific analyses the authors carried out in this\nregard. While the outcome of their effort has been negative, I believe these analyses shdoul be featured more\nprominently in the manuscript and require some clarifications as well as some extra effort. Regarding\nthe attempts to identify candidate leptophyte nuclear psbO genes and potential nucleomorph\n“RNApolB” genes, one should bear in mind that these genes are expected to harbour intronic regions\nthat disrupt the coding sequence. However, it is not clear from description of the search procedure\nemployed by the authors whether and how they accounted for the possibility of the coding sequences\nof the target genes being interrupted by introns, which obviously complicates retrieval of the\nsufficiently complete amino acid sequences from the metagenomic data. Next, it should be explicitly\nmentioned that the authors were looking for “RNApolB” genes specifically related to cryptophyte\nnucleomorphs (as sequences affiliated to homologs from chlorarachniophyte nuclemorphs would not\nbe god candidates for leptophyte nucleomorph genes). In fact, I am slightly confused by the authors\nusing the term “RNApolB” genes. Eukaryotes generally have three different homologs of the single\nprokaryotic RNApolB protein, corresponding to subunits of RNA polymerase I, II and III. So which\nprotein of those do the authors mean here?\n–Response: The reviewer raised several important points here, which we address one by one.\n1. “The methods section then indeed includes a section describing specific analyses the authors\ncarried out in this regard. While the outcome of their effort has been negative, I believe these\nanalyses shdoul be featured more prominently in the manuscript and require some clarifications\nas well as some extra effort.”\nWe agree, and the main text now includes a more detailed description of the search for sequences from\nthe host lineage (lines 277-317). Excitingly, following the reviewer’s next suggestion, we have now\ncharacterized the mitochondrial genome of one leptophyte with high confidence, by combining\nphylogenetic signal and distribution patterns (see response to next comment for more details). The\ndescription for the search for the host nuclear sequences in the main text is as follows (lines 279-286):\n“Plastid genomes do not necessarily mirror the long-term evolutionary trajectory of their host cell\nbecause of the complex history of endosymbioses2,4. In an effort to identify potential nuclear-encoded\nsequences for leptophytes, we searched the Arctic stations data—where the leptophyte abundance was\nthe highest—for psbO and 18S rDNA candidate genes (see Methods). The psbO gene is essential for\nphotosynthesis, it is always host-encoded and never found in non-photosynthetic organisms36.\nAlthough it is derived from the endosymbiont and thus would not be a good phylogenetic marker for\nthe host, our rationale was that it could pinpoint to host contigs that may contain additional genes.\nThese\nanalyses did not provide promising candidates for either gene”\n2. “Regarding the attempts to identify candidate leptophyte nuclear psbO genes and potential\nnucleomorph “RNApolB” genes, one should bear in mind that these genes are expected to\nharbour intronic regions that disrupt the coding sequence. However, it is not clear from\ndescription of the search procedure employed by the authors whether and how they accounted\nfor the possibility of the coding sequences of the target genes being interrupted by introns, which\nobviously complicates retrieval of the sufficiently complete amino acid sequences from the\nmetagenomic data.”\nWe agree with the reviewer that introns are a central component of the genomic landscape of unicellular\neukaryotes.\nRegarding psbO, we first searched the co-assembly of Arctic samples. While introns may have\ninterfered with gene detection, a more significant challenge is likely the substantially lower coverage\nof eukaryotic nuclear genomes overall. To investigate this, we used the curated psbO database generated\nby Pierella Karlusich et al. 2022 (https://doi.org/10.1111/1755-0998.13592), and retrieved the top 50\npsbO sequences from two metagenomes of Tara Station 194, where Lepto-01 ptMAG coverage ranged\nfrom 124× to 70×. This database is based on metatranscriptomic assemblies and thus avoids the issue\nof introns. Most psbO sequences had only a small number of metagenomic reads mapping to them per\nsample (median for the top 50 most abundant sequences = 3), except for those derived from highly\nabundant chlorophytes and ochrophytes. This indicates that nuclear genomes generally have much\nlower coverage than plastid genomes, likely contributing to our failure of retrieving the leptophytes\npsbO sequences.\nRegarding RNApolB, the gene database comes from metagenomic assemblies, thus may contain\nintrons, but this approach proved successful in targeting and recovering nearly one thousand eukaryotic\nMAGs from the sunlit oceans (https://doi.org/10.1016/j.xgen.2022.100123). In addition, while this is\nnot yet in the form of a preprint, we share here with the reviewer that we have also successfully\ncharacterized a major new clade of red-algal nucleomorph from the sunlit oceans using the same\nRNApolB gene database. These two surveys worked despite the occurrence of introns because as long\nas a fragment is long enough, it can be adequately placed in a global phylogeny to identify putative\nclades of interest. At least, this is our experience with the Tara Oceans data over a 5+ years period. As\na result, we believe that either (1) the leptophytes have a nucleomorph that did not have enough signal\nto be assembled in our Tara Oceans metagenomic survey (nucleomorphs have usually a similar\ncoverage as the nuclear genome, much less compared to the plastid and mitochondrial genomes), or (2)\nthe leptophytes lack a nucleomorph. Unfortunately, we could not answer this question in the present\nstudy. As a big follow-up effort, we ambition to reach the sequencing level needed to assemble a\nleptophyte nuclear genome using targeted filters. By doing so, we hope to be able to answer the pressing\nquestion of the nucleomorph.\n3. “Next, it should be explicitly mentioned that the authors were looking for “RNApolB” genes\nspecifically related to cryptophyte nucleomorphs (as sequences affiliated to homologs from\nchlorarachniophyte nuclemorphs would not be god candidates for leptophyte nucleomorph\ngenes).”\nWe have now clarified that we specifically looked for a nucleomorph related to cryptophytes (line 700-\n702):\n“Specifically, we surveyed the assembled RNApolB genes, following the protocol used to characterize\nptMAGs but this time using publicly available cryptophyte nucleomorph RNApolB genes as a\nreference.”\n4. “In fact, I am slightly confused by the authors using the term “RNApolB” genes. Eukaryotes\ngenerally have three different homologs of the single prokaryotic RNApolB protein,\ncorresponding to subunits of RNA polymerase I, II and III. So which protein of those do the\nauthors mean here?”\nWe are also aware that eukaryotes have 3 types of RNApolB (also 3 types of RNApolA), and in our\nprevious surveys (the published eukaryotic MAGs and the unpublished nucleomorph MAGs), each\nRNApolB homolog is an opportunity to identify and subsequently characterize a genome of eukaryotic\norigin. In previous work on eukaryotic MAGs, we concatenated the 3 types of RNApolB as well as the\n3 types of RNApolA to infer a phylogeny (see figure 2 of https://doi.org/10.1016/j.xgen.2022.100123).\nThe key point is that having multiple types of RNApolB (all being detectable with our dedicated HMM)\nis not an issue when screening for eukaryotic genomes across metagenomic assemblies. As a final note,\ncompared to psbO, a major advantage of RNApolB is its occurrence in all eukaryotes, not just those\nperforming photosynthesis.\n- Regarding the search for candidate leptophyte 18S rRNA gene: my own experience with metagenome\ndata analyses is such that particular 18S rRNA sequences are frequently missing from sequences\nassemblies despite the fact they are represented in the sequencing reads. Was the analysis of the V9\nmetabarcoding ASV sequences mentioned in lines 602-605 based directly on reads? Likely so, but this\nis not completely clear from the very brief description of the procedure. Regardless, I think it would\nmake sense to dig a bit deeper, and above all to test directly the most likely possibilities or the\nhypotheses raised by the authors themselves. Specifically, the authors should directly check the reads\nfrom the metagenomic samples that contain leptophyte sequences for the presence of 18S rRNA\nsignatures corresponding to the known uncultivated haptophyte-related lineages (presented in refs #42\nand #43) or to the CRY3 lineage. Next, there is a recent preprint by Romero et al. (bioRxiv,\nhttps://doi.org/10.1101/2025.03.26.645542) reporting on a systematic analysis of 18S rRNA sequences\nin metagenomic data and reporting in numerous novel eukaryote lineages. One is wondering whether\nthis study might help identify candidates for leptophyte 18S rRNA sequences. Finally, I believe it is\nlikely that at least partial mitochondrial genome sequences from leptophytes should be present in\nsamples containing their plastid genes, so I strongly encourage the authors to look for mitochondrial\ngenome sequences co-occurring with the leptophyte plastome sequences and representing\nphylogenetically separate lineages placed in the global tree such that they at least potentially may\ncorrespond to leptophyte mitochondria. The leptophyte story is clearly central to the whole paper and\nthis extra effort may make is stronger.\n–Response: The reviewer again made several useful suggestions. We address them one by one.\n1. Search for 18S rDNA gene\nThe reviewer is correct that our description of the 18S rDNA gene is rather brief, a point also raised by\nreviewer 3, and we apologise for the confusion. We performed a thorough survey to search for a putative\nleptophyte 18S rDNA gene which we describe below, along with a biological interpretation of the\nresults.\nFirst, we note that linking 18S rDNA sequences to a MAG is inherently challenging. In the case of\nLepto-01, we would expect the associated 18S rDNA sequence to correspond to a deep-branching\nlineage related to haptophytes, potentially within the HAP-4 clade\n(http://doi.org/10.1127/pip/2016/0052). Note that we initially considered CRY-3 a plausible candidate,\nbut subsequent results from the mitochondrial survey and phylogenetic analyses have now made this\nunlikely. Importantly, identifying such novel 18S sequences in targeted samples alone is insufficient to\nestablish a robust link to a MAG. Correlated abundance patterns across samples are also critical for\ninferring a link to the same biological entity.\nOur initial strategy was to retrieve 18S rDNA sequences from a co-assembly of samples where Lepto-\n01 was highly abundant. While we acknowledge that this approach can overlook many eukaryotic taxa,\nit is a promising method for detecting abundant taxa in the metagenomes, as demonstrated by the recent\nRomero et al. preprint (https://doi.org/10.1101/2025.03.26.645542), and by previous work\n(https://doi.org/10.1111/1755-0998.13147). Our rationale was that this targeted approach might yield a\nsmall, manageable set of near-full length candidate sequences for further investigation. However, this\nattempt did not result in any candidates for leptophytes, as all the 95 retrieved sequences were linked to\nwell established clades. This outcome could be due to the difference between abundance of the Lepto-\n01 plastid DNA and the host nuclear DNA in the same samples. That is, while the plastid DNA appears\nto be highly abundant in these samples, the host cells, and thus the host nuclear DNA, may be relatively\nrare. This interpretation is also supported by our failure to retrieve the candidate leptophyte psbO gene\nfrom the same coassembly. Furthermore, we show below (2. Search for leptophyte mitochondria)\nthat plastid DNA in Lepto-01 seems to be at least seven times more abundant than its mitochondrial\nDNA. It is therefore reasonable to infer that the nuclear DNA is even less represented in the\nmetagenomes.\nWe then turned to metabarcoding data. We followed a workflow established by a recent study\n(Zavadska et al 2024: https://doi.org/10.1371/journal.pone.0303697) to link protist MAGs with protist\nmetabarcodes. Note that this study demonstrated that while it is possible to infer a one-to-one link\nbetween a MAG and an OTU/ASV, it is not always the case. The authors also observed other patterns,\nsuch as multiple OTUs corresponding to one MAG, or vice versa, highlighting the challenges of linking\nmetabarcodes with MAGs. For our analyses, we retrieved 5,366 V9 ASVs from 15 samples with the\nhighest Lepto-01 abundance. These ASVs included a substantial amount of novel diversity (1,868 ASVs\n< 90% similar to reference sequences), as well as sequences similar to deep-branching haptophyte\nclades (such as HAP-4 and HAP-5). We attempted to match each ASV to leptophytes, by using their\nrelative abundance across the 15 samples to estimate a correlation coefficient (Spearman’s correlation)\nwith the relative and absolute abundance of the Lepto-01 ptMAG in the same samples. This resulted in\n13 and seven candidate ASVs respectively with a Spearman’s correlation value > 0.7. These ASVs were\ninvestigated further by BLASTing against the PR2 database and nt. However, none of the candidates\nwere suitable as matches with leptophytes (the top matches in each case were with cercozoan\nsequences).\nWe hypothesize that this outcome is due to an extra challenge in linking metabarcodes with plastid\nMAGs. The abundance ratio between the 18S rDNA gene and the rest of the nuclear DNA of a\npopulation of cells can be expected to remain constant across samples. However, the same cannot be\nsaid for the abundance ratio between the 18S rDNA gene and plastid DNA; the amount of plastid DNA\nin a cell can be expected to vary as a function of the number of plastids per cell, and the number of\ngenome copies per plastid. Several studies have shown that, at least for the green alga,\nChlamydomonas\nreinhardtii, light and nutrient conditions impact the ratio of ptDNA:nucDNA\n(http://doi.org/10.1104/pp.113.216291"}]

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