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Animals and fungi have radically distinct morphologies, yet both evolved within the same eukaryotic supergroup: Opisthokonta 1,2 . Here we reconstructed the trajectory of genetic changes that accompanied the origin of Metazoa and Fungi since the divergence of Opisthokonta with a dataset that includes four novel genomes from crucial positions in the Opisthokonta phylogeny. We show that animals arose only after the accumulation of genes functionally important for their multicellularity, a tendency that began in the pre-metazoan ancestors and later accelerated in the metazoan root. By contrast, the pre-fungal ancestors experienced net losses of most functional categories, including those gained in the path to Metazoa. On a broad-scale functional level, fungal genomes contain a higher proportion of metabolic genes and diverged less from the last common ancestor of Opisthokonta than did the gene repertoires of Metazoa. Metazoa and Fungi also show differences regarding gene gain mechanisms. Gene fusions are more prevalent in Metazoa, whereas a larger fraction of gene gains were detected as horizontal gene transfers in Fungi and protists, in agreement with the long-standing idea that transfers would be less relevant in Metazoa due to germline isolation 3-5 . Together, our results indicate that animals and fungi evolved under two contrasting trajectories of genetic change that predated the origin of both groups. The gradual establishment of two clearly differentiated genomic contexts thus set the stage for the emergence of Metazoa and Fungi., (© 2022. The Author(s).)

Heterotrophic lineages of stramenopiles exhibit enormous diversity in morphology, lifestyle, and habitat. Among them, the marine stramenopiles (MASTs) represent numerous independent lineages that are only known from environmental sequences retrieved from marine samples. The core energy metabolism characterizing these unicellular eukaryotes is poorly understood. Here, we used single-cell genomics to retrieve, annotate, and compare the genomes of 15 MAST species, obtained by coassembling sequences from 140 individual cells sampled from the marine surface plankton. Functional annotations from their gene repertoires are compatible with all of them being phagocytotic. The unique presence of rhodopsin genes in MAST species, together with their widespread expression in oceanic waters, supports the idea that MASTs may be capable of using sunlight to thrive in the photic ocean. Additional subsets of genes used in phagocytosis, such as proton pumps for vacuole acidification and peptidases for prey digestion, did not reveal particular trends in MAST genomes as compared with nonphagocytotic stramenopiles, except a larger presence and diversity of V-PPase genes. Our analysis reflects the complexity of phagocytosis machinery in microbial eukaryotes, which contrasts with the well-defined set of genes for photosynthesis. These new genomic data provide the essential framework to study ecophysiology of uncultured species and to gain better understanding of the function of rhodopsins and related carotenoids in stramenopiles.

Single-cell genomics (SCG) appeared as a powerful technique to get genomic information from uncultured organisms. However, SCG techniques suffer from biases at the whole genome amplification step that can lead to extremely variable numbers of genome recovery (5-100%). Thus, it is unclear how useful can SCG be to address evolutionary questions on uncultured microbial eukaryotes. To provide some insights into this, we here analysed 3 single-cell amplified genomes (SAGs) of the choanoflagellate Monosiga brevicollis, whose genome is known. Our results show that each SAG has a different, independent bias, yielding different levels of genome recovery for each cell (6-36%). Genes often appear fragmented and are split into more genes during annotation. Thus, analyses of gene gain and losses, gene architectures, synteny and other genomic features can not be addressed with a single SAG. However, the recovery of phylogenetically-informative protein domains can be up to 55%. This means SAG data can be used to perform accurate phylogenomic analyses. Finally, we also confirm that the co-assembly of several SAGs improves the general genomic recovery. Overall, our data show that, besides important current limitations, SAGs can still provide interesting and novel insights from poorly-known, uncultured organisms.