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Ocean color remote sensing has been used for more than 2 decades to estimate primary productivity. Approaches have also been developed to disentangle phytoplankton community structure based on spectral data from space, in particular when combined with in situ measurements of photosynthetic pigments. Here, we propose a new ocean color algorithm to derive the relative cell abundance of seven phytoplankton groups, as well as their contribution to total chlorophyll a (Chl a) at the global scale. Our algorithm is based on machine learning and has been trained using remotely sensed parameters (reflectance, backscattering, and attenuation coefficients at different wavelengths, plus temperature and Chl a) combined with an omics-based biomarker developed using Tara Oceans data representing a single-copy gene encoding a component of the photosynthetic machinery that is present across all phytoplankton, including both prokaryotes and eukaryotes. It differs from previous methods which rely on diagnostic pigments to derive phytoplankton groups. Our methodology provides robust estimates of the phytoplankton community structure in terms of relative cell abundance and contribution to total Chl a concentration. The newly generated datasets yield complementary information about different aspects of phytoplankton that are valuable for assessing the contributions of different phytoplankton groups to primary productivity and inferring community assembly processes. This makes remote sensing observations excellent tools to collect essential biodiversity variables (EBVs) and provide a foundation for developing marine biodiversity forecasts.

Phytoplankton account for >45% of global primary production, and have an enor-mous impact on aquatic food webs and on the entire Earth System. Their members are found among prokaryotes (cyanobacteria) and multiple eukaryotic lineages con-taining chloroplasts. Genetic surveys of phytoplankton communities generally consist of PCR amplification of bacterial (16S), nuclear (18S) and/or chloroplastic (16S) rRNA marker genes from DNA extracted from environmental samples. However, our appre-ciation of phytoplankton abundance or biomass is limited by PCR-amplification biases, rRNA gene copy number variations across taxa, and the fact that rRNA genes do not provide insights into metabolic traits such as photosynthesis. Here, we targeted the photosynthetic gene psbO from metagenomes to circumvent these limitations: the method is PCR-free, and the gene is universally and exclusively present in photosyn-thetic prokaryotes and eukaryotes, mainly in one copy per genome. We applied and validated this new strategy with the size-fractionated marine samples collected by Tara Oceans, and showed improved correlations with flow cytometry and microscopy than when based on rRNA genes. Furthermore, we revealed unexpected features of the ecology of these ecosystems, such as the high abundance of picocyanobacterial aggregates and symbionts in the ocean, and the decrease in relative abundance of phototrophs towards the larger size classes of marine dinoflagellates. To facilitate the incorporation of psbO in molecular- based surveys, we compiled a curated database of >18,000 unique sequences. Overall, psbO appears to be a promising new gene marker for molecular- based evaluations of entire phytoplankton communities This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Diatomic; grant agreement No. 835067). Additional funding is acknowledged from the FFEM - French Facility for Global Environment (Fonds Français pour l'Environnement Mondial), and the French Government “Investissements d’Avenir” Programmes MEMO LIFE (Grant ANR-10-LABX-54), Université de Recherche Paris Sciences et Lettres (PSL) (Grant ANR-1253 11-IDEX-0001-02), France Genomique (ANR-10-INBS-09), and OCEANOMICS (Grant ANR-11-BTBR-0008). JJPK acknowledges postdoctoral funding from the Fonds Français pour l’Environnement Mondial. RGD acknowledges a CNRS Momentum Fellowship, awarded 2019-2021 This article is contribution number 127 of Tara Oceans..-- 25 pages, 8 figures, 2 tables, supporting Information https://doi.org/10.1111/1755-0998.13592.-- Data availability statement: All datasets analysed for this study are of public access as described in Table 1. The curated psbO database was submitted to the EMBL-EBI repository BioStudies (www.ebi.ac.uk/biostudies) under accession S-BSST659. The 18S miTags data set covering size fractions between 0.8 and 2,000 µm was submitted to the same repository under accession S-BSST762. The Supporting Information tables for flow cytometry and optical microscopy as well as the protein sequences used for building the protein similarity networks are available at S-BSST761 With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S) Peer reviewed

Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles and help regulate climate. Although global surveys are starting to reveal ecological drivers underlying planktonic community structure and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here, we leveraged Tara Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network-the community interactome-and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar) and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change and forecasted the most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios while identifying plausible plankton bioindicators for ocean monitoring of climate change. International audience

ABSTRACT Diatoms are a major component of phytoplankton, believed to be responsible for around 20% of the annual primary production on Earth. As abundant and ubiquitous organisms, they are known to establish biotic interactions with many other members of plankton. Through analyses of cooccurrence networks derived from the Tara Oceans expedition that take into account both biotic and abiotic factors in shaping the spatial distributions of species, we show that only 13% of diatom pairwise associations are driven by environmental conditions; the vast majority are independent of abiotic factors. In contrast to most other plankton groups, on a global scale, diatoms display a much higher proportion of negative correlations with other organisms, particularly toward potential predators and parasites, suggesting that their biogeography is constrained by top-down pressure. Genus-level analyses indicate that abundant diatoms are not necessarily the most connected and that species-specific abundance distribution patterns lead to negative associations with other organisms. In order to move forward in the biological interpretation of cooccurrence networks, an open-access extensive literature survey of diatom biotic interactions was compiled, of which 18.5% were recovered in the computed network. This result reveals the extent of what likely remains to be discovered in the field of planktonic biotic interactions, even for one of the best-known organismal groups. IMPORTANCE Diatoms are key phytoplankton in the modern ocean that are involved in numerous biotic interactions, ranging from symbiosis to predation and viral infection, which have considerable effects on global biogeochemical cycles. However, despite recent large-scale studies of plankton, we are still lacking a comprehensive picture of the diversity of diatom biotic interactions in the marine microbial community. Through the ecological interpretation of both inferred microbial association networks and available knowledge on diatom interactions compiled in an open-access database, we propose an ecosystems approach for exploring diatom interactions in the ocean. Diatoms are key phytoplankton in the modern ocean that are involved in numerous biotic interactions, ranging from symbiosis to predation and viral infection, which have considerable effects on global biogeochemical cycles. However, despite recent large-scale studies of plankton, we are still lacking a comprehensive picture of the diversity of diatom biotic interactions in the marine microbial community. Through the ecological interpretation of both inferred microbial association networks and available knowledge on diatom interactions compiled in an open-access database, we propose an ecosystems approach for exploring diatom interactions in the ocean.

Microbial communities in the world ocean are affected strongly by oceanic circulation, creating characteristic marine biomes. The high connectivity of most of the ocean makes it difficult to disentangle selective retention of colonizing genotypes (with traits suited to biome specific conditions) from evolutionary selection, which would act on founder genotypes over time. The Arctic Ocean is exceptional with limited exchange with other oceans and ice covered since the last ice age. To test whether Arctic microalgal lineages evolved apart from algae in the global ocean, we sequenced four lineages of microalgae isolated from Arctic waters and sea ice. Here we show convergent evolution and highlight geographically limited HGT as an ecological adaptive force in the form of PFAM complements and horizontal acquisition of key adaptive genes. Notably, ice-binding proteins were acquired and horizontally transferred among Arctic strains. A comparison with Tara Oceans metagenomes and metatranscriptomes confirmed mostly Arctic distributions of these IBPs. The phylogeny of Arctic-specific genes indicated that these events were independent of bacterial-sourced HGTs in Antarctic Southern Ocean microalgae. International audience

Abstract Marine planktonic eukaryotes play a critical role in global biogeochemical cycles and climate. However, their poor representation in culture collections limits our understanding of the evolutionary history and genomic underpinnings of planktonic ecosystems. Here, we used 280 billion metagenomic reads from 143 Tara Oceans stations to reconstruct and manually curate more than 700 abundant and widespread eukaryotic metagenome-assembled genomes ranging from 10 Mbp to up to 1.3 Gbp. The resulting non-redundant genomic resource of 25 billion nucleotides that describe 10 million genes covers a wide range of poorly characterized unicellular and multicellular eukaryotic lineages that complement the long-standing contributions of culture efforts to survey the tree of marine life while better representing plankton from the open ocean. Phylogeny of the DNA-dependent RNA polymerase placed this genomic resource in a comprehensive evolutionary framework that provided insights into the relationships of eukaryotic supergroups. From there, classification of unicellular eukaryotic plankton based on functions encoded in their genes revealed four major groups connecting distantly related lineages such as the diatoms and green algae. There has been a recurrent problem in understanding the interplay between eukaryotes’ vertical evolution and their phenotype. By disentangling phylogenetic signals from functional trends with genomics, we found that neither the classical trophic mode of plankton nor its vertical evolutionary history could fully explain the genomic functional landscape of marine eukaryotes that coexisted for millions of years. Cover Navigating on the map of plankton genomics with Tara Oceans and anvi’o: a comprehensive genome-resolved metagenomic survey dedicated to eukaryotic plankton.