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.
DNA viruses have a major influence on the ecology and evolution of cellular organisms1–4, but their overall diversity and evolutionary trajectories remain elusive5. Here we carried out a phylogeny-guided genome-resolved metagenomic survey of the sunlit oceans and discovered plankton-infecting relatives of herpesviruses that form a putative new phylum dubbed Mirusviricota. The virion morphogenesis module of this large monophyletic clade is typical of viruses from the realm Duplodnaviria6, with multiple components strongly indicating a common ancestry with animal-infecting Herpesvirales. Yet, a substantial fraction of mirusvirus genes, including hallmark transcription machinery genes missing in herpesviruses, are closely related homologues of giant eukaryotic DNA viruses from another viral realm, Varidnaviria. These remarkable chimaeric attributes connecting Mirusviricota to herpesviruses and giant eukaryotic viruses are supported by more than 100 environmental mirusvirus genomes, including a near-complete contiguous genome of 432 kilobases. Moreover, mirusviruses are among the most abundant and active eukaryotic viruses characterized in the sunlit oceans, encoding a diverse array of functions used during the infection of microbial eukaryotes from pole to pole. The prevalence, functional activity, diversification and atypical chimaeric attributes of mirusviruses point to a lasting role of Mirusviricota in the ecology of marine ecosystems and in the evolution of eukaryotic DNA viruses.
Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.
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