Sofia Medvedeva

Jiarui Sun

Natalya Yutin

Eugene V Koonin

Takuro Nunoura
email: takuron@jamstec.go.jp

Christian Rinke
email: c.rinke@uq.edu.au

Mart Krupovic
email: mart.krupovic@pasteur.fr

Three families of Asgard archaeal viruses identified in metagenome-assembled genomes

Asgardarchaeota harbour many eukaryotic signature proteins and are widely considered to represent the closest archaeal relatives of eukaryotes. Whether similarities between Asgard archaea and eukaryotes extend to their viromes remains unknown. Here we present 20 metagenome-assembled genomes of Asgardarchaeota from deep-sea sediments of the basin off the Shimokita Peninsula, Japan. By combining a CRISPR spacer search of metagenomic sequences with phylogenomic analysis, we identify three family-level groups of viruses associated with Asgard archaea. The first group, verdandiviruses, includes tailed viruses of the class Caudoviricetes (realm Duplodnaviria); the second, skuldviruses, consists of viruses with predicted icosahedral capsids of the realm Varidnaviria; and the third group, wyrdviruses, is related to spindle-shaped viruses previously identified in other archaea. More than 90% of the proteins encoded by these viruses of Asgard archaea show no sequence similarity to proteins encoded by other known viruses. Nevertheless, all three proposed families consist of viruses typical of prokaryotes, providing no indication of specific evolutionary relationships between viruses infecting Asgard archaea and eukaryotes. Verdandiviruses and skuldviruses are likely to be lytic, whereas wyrdviruses potentially establish chronic infection and are released without host cell lysis. All three groups of viruses are predicted to play important roles in controlling Asgard archaea populations in deep-sea ecosystems.

Introduction

Asgard archaea are an expansive group of metabolically versatile archaea that thrive primarily in anoxic sediments around the globe [1][2][3][4][5][6][7][8][9] . Based on phylogenomic analyses, asgardarchaea have been originally classified into multiple phylum-level lineages, including Lokiarchaeota, Thorarchaeota, Odinarchaeota, Heimdallarchaeota, Helarchaeota, Sifarchaeota, Wukongarchaeota and several others, most of which were named after Norse gods 1,5,7,[9][10][11][12] . Recently, taxonomic rank normalization using relative evolutionary divergence has suggested that asgardarchaea represent a phylum, tentatively named Asgardarchaeota, including the classes Lokiarchaeia, Thorarchaeia, Odinarchaeia, Heimdallarchaeia, Sifarchaeia, Hermodarchaeia, Sifarchaeia, Baldrarchaeia, Wukongarchaeia and Jordarchaeia, with the other lineages classified as lower-rank taxa within the classes 8,13 . The vast majority of asgardarchaea have been discovered through metagenomics, whereas only one species has been isolated and successfully grown in the laboratory 14 . Asgardarchaea gained prominence due to their inferred key role in the origin of eukaryotes 15 . Indeed, Heimdallarchaeia form a sister group to eukaryotes in most phylogenetic analyses 1,5 , although alternative phylogenies have also been presented [START_REF] Da Cunha | Asgard archaea do not close the debate about the universal tree of life topology[END_REF][START_REF] Da Cunha | Lokiarchaea are close relatives of Euryarchaeota, not bridging the gap between prokaryotes and eukaryotes[END_REF] . Compared to other archaea, asgardarchaea encode a substantially expanded set of eukaryotic signature proteins, including many proteins implicated in membrane trafficking, vesicle formation and transport, cytoskeleton formation, the ubiquitin network and other processes characteristic of eukaryotes 1,5 . A tantalizing question is whether eukaryotes also inherited viruses and other types of mobile genetic elements (MGE) from the asgardarchaea?

Viruses infecting archaea are remarkably diverse, both in terms of their genome sequences and virion structures [START_REF] Baquero | Structure and assembly of archaeal viruses[END_REF][START_REF] Prangishvili | The enigmatic archaeal virosphere[END_REF][START_REF] Dellas | Archaeal Viruses: Diversity, Replication, and Structure[END_REF] . Some archaeal viruses, in particular those with icosahedral virions, are evolutionarily related to bacterial and eukaryotic viruses, but the majority of archaeal virus groups are specific to archaea, with no identifiable relatives in the two other domains. Archaea-specific viruses often have oddshaped virions, which resemble lemons, champagne bottles or droplets [START_REF] Prangishvili | The enigmatic archaeal virosphere[END_REF] . Most archaeal viruses have been thus far isolated from hyperthermophilic or halophilic hosts, with only a handful of virus species described for methanogenic and ammonia-oxidizing mesophilic archaea [START_REF] Baquero | Structure and assembly of archaeal viruses[END_REF] . No viruses infecting asgardarchaea have been isolated, primarily due to the inherent difficulty to propagate asgardarchaeal hosts. Nevertheless, analysis of the CRISPR-Cas loci in the genomes of asgardarchaea revealed a remarkable diversity of defense systems in these organisms [START_REF] Makarova | Unprecedented diversity of unique CRISPR-Cas-related systems and Cas1 homologs in Asgard archaea[END_REF] , implying a rich asgardarchaeal virome. CRISPR arrays are archives of past viral/MGE encounters, which can be harnessed to uncover the associations between viruses and their hosts. Indeed, matching the CRISPR spacers from a known organism to viruses with unknown hosts is widely used for host assignment for viruses discovered by metagenomics and arguably is the most straightforward and efficient approach to identify the hosts of viruses infecting prokaryotes [START_REF] Coclet | Global overview and major challenges of host prediction methods for uncultivated phages[END_REF] .

Here we harness CRISPR spacer sequences from the sequenced asgardarchaeal genomes to search for viruses infecting these organisms and describe three distinct family-level groups of Asgard-associated viruses, all of which display typical features of viruses infecting bacteria or archaea.

Results

To search for viruses infecting asgardarchaea, we sequenced 12 metagenomes constructed from total environmental DNA directly extracted from the subseafloor sediments originating off the Shimokita Peninsula, Japan (site C9001, water depth 1,180 m) [START_REF] Nunoura | Variance and potential niche separation of microbial communities in subseafloor sediments off Shimokita Peninsula, Japan[END_REF] and representing different sediment depths ranging from 0.91 to 363.3 meters below the seafloor (mbsf). Asgardarchaeal metagenome-assembled genomes (MAGs) were assembled from 7 of the 12 samples. A total of 20 Asgardarchaeota MAGs, including 12 Lokiarchaeia, 2 Thorarchaeia and 6 Heimdallarchaeia were analyzed in this study (Fig. 1), with an estimated completeness of 65.95±17.93, estimated quality of 54.68±15.78, and GC content of 32.78±3.99 (Table S1).

To assign the putative viral genomes to asgardarchaeal hosts, we assembled a dataset of CRISPR spacers from asgardarchaeal MAGs assembled in this study as well as those reported previously (Fig. 2, Table S2). Analysis of the Asgard CRISPR arrays allowed us to define Asgard-specific CRISPR repeat sequences, which were used to identify additional CRISPR arrays from the contigs obtained from our sediment samples (Fig. 2a; see Methods for details). In total, our CRISPR spacer dataset (Fig. 2b, Supplementary Data 1), included 2,532 spacers assigned to different Asgardarchaota lineages, with Lokiarchaeia contributing the highest number of spacers (Fig. 2c). All spacers were then used to search for protospacers in the 20 assembled MAGs and putative virus genomes from our dataset as well as contigs from GenBank and JGI sequence databases. In total, 14 contigs could be assigned to asgardarchaeal hosts based on CRISPR spacer matches with estimated false positive rate of 0.00276 (see Methods for details, Extended Data 1). By contrast, none of the contigs was targeted by spacers from the CRISPRHost database (675,911 spacers) and only two, likely false positive, spacers were identified in the CRISPR Spacer Database and Exploration Tool (11,674,395 spacers; see Methods).

Eight of the putative viral genomes originated from the metagenomes sequenced in this study (from depths ranging from 0.91 to 87.7 mbsf), whereas six additional genomes were recovered from datasets sequenced previously, including anoxic subseafloor sediment samples from two Pacific Ocean sites, the Hikurangi Subduction Margin (144.3 mbsf) 8 and Cascadia Margin (2 mbsf) [START_REF] Glass | Microbial metabolism and adaptations in Atribacteria-dominated methane hydrate sediments[END_REF] , and one Indian Ocean site, Sumatra Forearc (1.6-6.07 mbsf; PRJNA367446). Each genome was targeted (≥90% identity between spacer and protospacer) by 1-6 CRISPR spacers assigned to putative Asgard classes Lokiarchaeia, Thorarchaeia, and Heimdallarchaeia (Fig. 1, Tables S3 andS4). Based on the conservation of viral hallmark proteins, including major capsid proteins (MCP), seven of the genomes were unequivocally identified as belonging to viruses from three unrelated groups (Fig. 345), whereas the remaining seven could represent either unknown viruses or other types of mobile genetic elements (MGEs; Fig. S1, see below). The viral dataset was further enriched by searching the JGI and GenBank sequence databases for related contigs. As a result, we collected 21 contig representing three groups of asgardarchaeal viruses originating from seven geographically remote locations (Fig. 6a). Further analyses using CRISPR-based (SpacePHARER) and kmer-based (WiSH and PHIST) methods confirmed the association of the 21 contigs with asgardarchaeal hosts (see Methods, Tables S3 andS5). Network analysis of these viral genomes together with the bacterial and archaeal virus genomes available in RefSeq showed that the three Asgard virus groups are disconnected from each other as well as from other known viruses (Fig. 6b).

Verdandiviruses are tailed viruses of the

Caudoviricetes

Three of the genomes, VerdaV1, -2 and -3, assembled from the Shimokita dataset, encode the hallmark proteins specific to viruses of the class Caudoviricetes, the most widespread, environmentally abundant and genetically diverse group of viruses [START_REF] Dion | Phage diversity, genomics and phylogeny[END_REF][START_REF] Iranzo | The double-stranded DNA virosphere as a modular hierarchical network of gene sharing[END_REF] . Members of the Caudoviricetes infect bacteria and archaea, and have characteristic virions consisting of an icosahedral capsid and a helical tail attached to one of the capsid vertices. Caudoviricetes together with eukaryotic herpesviruses form the realm Duplodnaviria [START_REF] Koonin | Global Organization and Proposed Megataxonomy of the Virus World[END_REF] . Similar to previously characterized bacterial and archaeal Caudoviricetes [START_REF] Baquero | Structure and assembly of archaeal viruses[END_REF] , each of the three virus genomes encodes the HK97-like MCP, large subunit of the terminase (genome packaging ATPase-nuclease), the portal protein as well as several other structural proteins, including tail components (Fig. 3a). Structural modeling of the VerdaV1 MCP using RoseTTAFold [START_REF] Baek | Accurate prediction of protein structures and interactions using a three-track neural network[END_REF] , yielded a model with the canonical HK97-like fold (Fig. 3b).

The VerdaV1 (19.9 kb) and VerdaV2 (19.5 kb) genomes were assembled as circular contigs (Table S3), suggesting that they correspond to complete, terminally redundant virus genomes, whereas VerdaV3 (15.4 kb) likely represents a partial genome. Comparative genomics analysis showed that VerdaV1, -2 and -3 belong to the same virus group (Fig. 3a), which we refer to as 'verdandiviruses' (for Verdandi, one of the three Norns, the most powerful beings in Norse mythology that govern the lives of gods and mortals). Given that the three genomes were identified in different sediment depths of offshore Shimokita Peninsula (at 18.7, 59.5 and 87.7 mbsf; Table S3), we addressed the possibility that related viruses could also be detected in samples from other depths. To this end, we performed BLASTP searches (E-value cutoff of 1e-05) queried with the corresponding MCP sequences against the assembled sequences from samples retrieved along the depth gradient. The analysis yielded six additional viral contigs and showed that related MCPs (and viruses) are also present in sediment samples from 0.9, 9.3 and 30.8 mbsf, indicating a broad distribution of verdandiviruses through the sediment column. One of the retrieved contigs (VerdaV4; 20.6 kb) was found to be circular and thus also represents a complete virus genome. Furthermore, searches against the GenBank and JGI sequence databases yielded eight hits to virus-like contigs affiliated to asgardarchaea (Table S3). Five of the MCPs were encoded within large contigs (>10 kb) including two (Ga0114925_10000341 and Ga0114923_10001063 [VerdaV5 and VerdaV6, respectively]) circular ones. Notably, VerdaV5 was also targeted by a CRISPR spacer from a recently described Asgardarchaeota MAG 1 , further supporting the host assignment for the Verdandivirus group (Fig. 3a, Table S3). Finally, we identified a partial provirus related to verdandiviruses integrated in a large genomic contig of Lokiarchaeia (Extended Data 3). The same contig contained cellular genes unequivocally belonging to Asgardarchaeota (98-99% protein identity), including those encoding ribosomal proteins. Verdandivirus contigs were recovered from four geographically remote sampling sites (Fig. 6a) and maximum likelihood phylogenetic analysis of the MCPs revealed an overall biogeographic clustering of verdandiviruses (Fig. 3c).

Although virus-encoded homologs could be identified for only 2% (7 out of 298) of verdandivirus proteins by blastp searches (E=1e-05), functional annotation for some of the other proteins was enabled by sensitive profile-profile comparisons, in which HK97-like MCP and TerL MCP were readily identified with highly significant scores (Fig. S2, Table S5). Verdandiviruses display considerable sequence conservation within the capsid formation and genome packaging modules (Fig. 3a). Notably, upstream of the MCP, all viruses carry a gene encoding a putative capsid stabilization protein distantly related to the corresponding protein of marine siphoviruses, e.g., TW1 [START_REF] Wang | Structure of the Marine Siphovirus TW1: Evolution of Capsid-Stabilizing Proteins and Tail Spikes[END_REF] , which might be important for maintaining capsid integrity under high hydrostatic pressures of the deep-sea ecosystems. Verdandiviruses encode tail proteins most closely similar to those of siphoviruses, including the major tail protein, tail tape measure protein and a baseplate hub protein with an adhesin domain, suggesting that verdandiviruses possess flexible, noncontractile tails. In most of these viruses, the tape measure protein is relatively short (median length 259 aa), suggesting that the tails themselves are short as well. Assuming ~1.5 Å of tail length per amino acid residue of tape measure protein [START_REF] Hendrix | Tail length determination in double-stranded DNA bacteriophages[END_REF][START_REF] Mahony | Functional and structural dissection of the tape measure protein of lactococcal phage TP901-1[END_REF] , the median tail length of verdandiviruses is predicted to be ~39 nm. The genes encoding tail proteins display low sequence conservation, whereas gene contents downstream of the tail modules are distinct in most of the identified viruses (Fig. 3a). Differences in the tail modules might correspond to different host ranges of the corresponding viruses. Indeed, whereas VerdaV1 and VerdaV5 were matched by CRISPR spacers from Lokiarchaeia, VerdaV2 and VerdaV3 are predicted to infect Thorarchaeia (Table S3). The distinct conservation patterns of the capsid and tail modules likely reflect modular evolution of these asgardarchaeal virus genomes, a common trait in bacterial and archaeal members of the Caudoviricetes [START_REF] Pope | Whole genome comparison of a large collection of mycobacteriophages reveals a continuum of phage genetic diversity[END_REF][START_REF] Krupovic | Comparative analysis of the mosaic genomes of tailed archaeal viruses and proviruses suggests common themes for virion architecture and assembly with tailed viruses of bacteria[END_REF] .

Verdandiviruses do not encode any proteins implicated in virus genome replication, and thus, can be predicted to fully rely on the hosts for this process. Complete dependence on the host replication machinery is common among archaeal viruses with small and midsized genomes [START_REF] Krupovic | Viruses of archaea: Structural, functional, environmental and evolutionary genomics[END_REF] , in particular, for the tailed viruses of haloarchaea and methanogens in the families Saparoviridae, Suolaviridae, Leisingerviridae and Anaerodiviridae [START_REF] Liu | Diversity, taxonomy, and evolution of archaeal viruses of the class Caudoviricetes[END_REF] . Verdandiviruses encode predicted DNA-binding proteins with Zn-finger and helix-turnhelix motifs, which could participate in recruitment of the host replication and transcription machineries. Indeed, in the case of hyperthermophilic archaeal virus SIRV2, a viral helix-turn-helix protein has been shown to recruit the host DNA sliding clamp protein, a known interaction partner for many other components of the host replisome [START_REF] Gardner | Protein-protein interactions leading to recruitment of the host DNA sliding clamp by the hyperthermophilic Sulfolobus islandicus rod-shaped virus 2[END_REF] .

All complete verdandivirus genomes encompass arrays of short genes encoding predicted small, poorly conserved proteins, some of which are adjacent to genes encoding predicted transcriptional regulators (Fig. 3a). Similar to many bacterial viruses of the Caudoviricetes [START_REF] Gussow | Machine-learning approach expands the repertoire of anti-CRISPR protein families[END_REF][START_REF] Li | Anti-CRISPRs go viral: The infection biology of CRISPR-Cas inhibitors[END_REF] , some of these small, fast evolving genes could encode antidefense, in particular, anti-CRISPR proteins.

Skuldviruses: tailless icosahedral viruses of asgardarchaea

One of the contigs from asgardarchaeal MAGs assembled from anoxic sediments from the Hikurangi subduction margin 8 , SkuldV1, targeted by two asgardarchaeal spacers (Table S3), encodes a double jelly-roll (DJR) MCP (Fig. 4a), a hallmark of viruses of the realm Varidnaviria, an expansive assemblage of viruses evolutionarily and structurally unrelated to duplodnaviruses [START_REF] Koonin | Global Organization and Proposed Megataxonomy of the Virus World[END_REF] . Varidnaviruses are environmentally abundant and infect hosts from all domains of life [START_REF] Koonin | Global Organization and Proposed Megataxonomy of the Virus World[END_REF][START_REF] Krupovic | Virus evolution: how far does the double beta-barrel viral lineage extend?[END_REF] . Sequence searches with the SkuldV1 MCP led to the identification of two additional contigs, one from our dataset (SkuldV2) and the other one from the GenBank database (JABUBK010000319, hereinafter referred to as SkuldV3). The latter contig was obtained from subseafloor sediments from the Cascadia Margin (Ocean Drilling Program, site 1244) in the Pacific Ocean [START_REF] Glass | Microbial metabolism and adaptations in Atribacteria-dominated methane hydrate sediments[END_REF] and is targeted by four spacers from our dataset. SkuldV1 and SkuldV3 were assembled as circular contigs and thus correspond to complete virus genomes (Fig. 4a). In addition to the DJR MCP, the vast majority of varidnaviruses encode genome packaging ATPases of the FtsK-HerA superfamily [START_REF] Hong | A structural model of the genome packaging process in a membrane-containing double stranded DNA virus[END_REF] . A homolog of such ATPase was identified in all three SkuldV genomes, indicating that they are bona fide members of the realm Varidnaviria. We propose referring to this group of viruses as 'Skuldviruses' (for Skuld, another of the Norns).

The vast majority of skuldvirus proteins (97%; 66 of the 68 proteins) show no similarity to proteins encoded by other known viruses. Network analysis using CLANS [START_REF] Frickey | CLANS: a Java application for visualizing protein families based on pairwise similarity[END_REF] showed that the skuldvirus MCPs form a cluster separate from the previously characterized [START_REF] Yutin | Vast diversity of prokaryotic virus genomes encoding double jelly-roll major capsid proteins uncovered by genomic and metagenomic sequence analysis[END_REF] groups of DJR MCPs (Fig. 4b). Nevertheless, profileprofile comparisons showed that they are most closely related to the corresponding proteins of prokaryotic viruses of the families Corticoviridae (bacteriophage PM2: HHsearch probability of 98.3), Turriviridae (archaeal virus STIV: HHsearch probability of 97.8) and Tectiviridae (bacteriophage PRD1: HHsearch probability of 96.2) (Fig. S3), whereas eukaryotic viruses with DJR MCPs were recovered with considerably lower scores (Phycodnaviridae, Pyramimonas orientalis virus: HHsearch probability of 83.4). Structural comparison of the SkuldV1 MCP model obtained using RoseTTAFold [START_REF] Baek | Accurate prediction of protein structures and interactions using a three-track neural network[END_REF] (Fig. 4b) further showed that it is most similar to the MCP of Pseudoalteromonas phage PM2 [START_REF] Abrescia | Insights into virus evolution and membrane biogenesis from the structure of the marine lipidcontaining bacteriophage PM2[END_REF] , a prototype of the Corticoviridae [START_REF] Oksanen | ICTV Virus Taxonomy Profile: Corticoviridae[END_REF] , which is widespread in marine ecosystems [START_REF] Krupovic | Putative prophages related to lytic tailless marine dsDNA phage PM2 are widespread in the genomes of aquatic bacteria[END_REF] . Nevertheless, skuldviruses do not share genes with other known viruses other than those encoding the MCP and the genome packaging ATPase. Corticoviruses, turriviruses and tectiviruses belong to the class Tectiliviricetes [START_REF] Koonin | Global Organization and Proposed Megataxonomy of the Virus World[END_REF] . We propose that skuldviruses represent a separate virus family within the Tectiliviricetes.

Corticoviruses employ a rolling circle mechanism for genome replication and encode characteristic HUH superfamily endonucleases [START_REF] Kazlauskas | Multiple origins of prokaryotic and eukaryotic single-stranded DNA viruses from bacterial and archaeal plasmids[END_REF] . No such genes or other putative replication genes were identified in skuldviruses. Instead, all three skuldviruses encode a protein related to the A subunit of type IIB topoisomerases, such as topoisomerase VI. The latter enzyme consists of two distinct subunits, A and B, with the catalytic tyrosine residue responsible for DNA nicking located in the A subunit. Standalone A subunits, dubbed Topo mini-A, have been recently discovered in diverse bacterial and archaeal MGEs [START_REF] Takahashi | Expanding the type IIB DNA topoisomerase family: identification of new topoisomerase and topoisomerase-like proteins in mobile genetic elements[END_REF] , but the functions of these proteins remain unknown. In the maximum likelihood phylogeny of Topo mini-A homologs, skuldvirus proteins form a clade with homologs from methanogenic and ammonia-oxidizing archaea (Extended Data 4). The skuldviral Topo mini-A might function as a replication protein, possibly initiating the rolling circle replication of the circular skuldvirus genomes, in a manner analogous to the HUH endonuclease.

Wyrdviruses are related to spindle-shaped archaeal viruses

One of the contigs from asgardarchaeal MAGs assembled from the Hikurangi Subduction Margin 8 , WyrdV1 (15,570 bp), targeted by one CRISPR spacer from our collection, was found to encode two homologs of the MCPs specific to spindle-shaped archaeal viruses [START_REF] Krupovic | Unification of the globally distributed spindle-shaped viruses of the Archaea[END_REF] . In particular, the closest homolog was found in haloarchaeal virus His1 (family Halspiviridae; Extended Data 5) [START_REF] Bath | His1 and His2 are distantly related, spindle-shaped haloviruses belonging to the novel virus group[END_REF] . His1-like MCPs are ~80 aa-long and contain two hydrophobic segments predicted to be membrane spanning domains [START_REF] Krupovic | Unification of the globally distributed spindle-shaped viruses of the Archaea[END_REF] and in all spindle-shaped viruses playing key roles in virion structure and assembly [START_REF] Wang | Spindle-shaped archaeal viruses evolved from rod-shaped ancestors to package a larger genome[END_REF] . BLASTP searches using the WyrdV1 MCP as a query against the JGI and GenBank databases identified eight additional contigs (Fig. 5). All these contigs shared several genes encoding a morphogenetic module, including the MCP and receptor-binding adhesin, which in fuselloviruses and halspiviruses is located at one of the pointed ends of the virion [START_REF] Hong | Lemon-shaped halo archaeal virus His1 with uniform tail but variable capsid structure[END_REF][START_REF] Quemin | Sulfolobus Spindle-Shaped Virus 1 Contains Glycosylated Capsid Proteins, a Cellular Chromatin Protein, and Host-Derived Lipids[END_REF] . In addition, all these viruses encode a AAA+ ATPase, which in profile-profile comparisons showed the highest similarity to the morphogenesis (pI) proteins of bacterial filamentous phages (order Tubulavirales) [START_REF] Roux | Cryptic inoviruses revealed as pervasive in bacteria and archaea across Earth's biomes[END_REF] . This ATPase is responsible for the extrusion of the viral genome through the cellular membrane during virion assembly [START_REF] Straus | Filamentous bacteriophage proteins and assembly[END_REF] . We propose referring to this group of viruses as 'wyrdviruses' (for Wyrd [Urðr], the third Norn). The homology between the tubulaviral and wyrdviral ATPases suggests that virion assembly of wyrdviruses is mechanistically similar to the extrusion of filamentous bacteriophages. Indeed, spindle-shaped viruses infecting other archaea are released from the host without causing the cell lysis through a budding-like mechanism [START_REF] Wang | Spindle-shaped archaeal viruses evolved from rod-shaped ancestors to package a larger genome[END_REF][START_REF] Kim | Spindle-shaped viruses infect marine ammonia-oxidizing thaumarchaea[END_REF][START_REF] Quemin | Eukaryotic-like virus budding in Archaea[END_REF] . Notably, some spindle-shaped viruses encode a single MCP (e.g., halspiviruses), whereas others encode two paralogous MCP (e.g., fuselloviruses). Similarly, wyrdviruses encode either one or two MCP paralogs (Fig. 5).

Similar to halspiviriruses and thaspiviruses, two of the contigs, Ga0209633_10003833 and Ga0209976_10001089, to which we refer to as WyrdV2 and WyrdV3, respectively, contained terminal inverted repeats (TIR), indicating that these are (nearly) complete genomes. By contrast, contigs JABUBK010000290 and JABUBK010000290, herein referred to as WyrdV4 and WyrdV5, respectively, contained direct terminal repeats, indicative of the completeness and circular structure of the genomes, resembling fuselloviruses. Consistent with the different genome structures, WyrdV2 and WyrdV3 (and halspiviruses) encode protein-primed family B DNA polymerases, whereas WyrdV4 and WyrdV5 encode rolling circle replication initiation endonucleases of the HUH superfamily (Fig. 5). Notably, WyrdV4, in addition, encodes Topo mini-A. The latter does not cluster with homologs from skuldviruses, but instead forms a clade with the Topo mini-A from the unassigned asgardarchaeal MGEs 10H_0 and 7H_42 (Extended Data 4). Contigs Ga0209976_10001631 (WyrdV6) and Ga0209976_10001236 (WyrdV7) also encode DNA polymerases and likely are linear, nearly complete viral genomes (Fig. 5). Remarkably, the DNA polymerase encoded by WyrdV7 is not orthologous to those of WyrdV2, WyrdV3 and WyrdV6 (Fig. 5). The latter group is most closely related (~30% identity) to the corresponding protein of an uncultured virus (MW522971) associated with Altiarchaeota [START_REF] Rahlff | Lytic archaeal viruses infect abundant primary producers in Earth's crust[END_REF] , whereas the former protein is most similar to the DNA polymerase encoded by the spindleshaped virus infecting marine Nitrososphaeria 55 (Table S3).

Ga0209977_10002196 and Ga0209976_10004438 are partial genomes that lack the region encompassing the replication modules. Notably, WyrdV1 lacks either the polymerase or the rolling circle endonuclease gene and instead at the equivalent locus contains an array of short genes, some of which might encode replication initiators. Similar dramatic variation in gene content has been previously observed only in haloarchaeal viruses of the family Pleolipoviridae, where members of three genera encode non-homologous genome replication proteins [START_REF] Bamford | ICTV Virus Taxonomy Profile: Pleolipoviridae[END_REF] . Our present observations further illuminate the remarkable plasticity of the genome replication modules and genome structures in relatively closely related archaeal viruses, in general, and in wyrdviruses, in particular.

Enigmatic MGEs and auxiliary genes of asgardarchaeal viruses

In addition to the three groups of viruses, we identified seven other contigs (7H_11, 8H_18, 8H_67, 10H_0, 7H_42, Ga0114923_10000127 and Ga0209976_10000148) targeted by asgardarchaeal CRISPR spacers (Table S3). Four of these contigs, 7H_11, 8H_18, 10H_0 and Ga0114923_10000127, were assembled as circular molecules and likely represent complete MGE genomes of 8,776 bp, 8,776 bp, 84,544 bp and 58,806 bp, respectively, whereas Ga0209976_10000148 (48,997 bp), 7H_42 (44,162 bp) and 8H_67 (13,282 bp) appeared to be partial. The seven contigs do not encode identifiable homologs of major capsid proteins of known viruses and are likely to represent either unknown viruses or non-viral MGEs, such as plasmids (see Supplementary text for description of the asgardarchaeal MGEs). Some of the asgardarchaeal MGEs and viruses encode auxiliary functions, including metabolic genes, such as phosphoadenosine phosphosulfate (PAPS) reductase, which could facilitate sulfur metabolism and/or synthesis of sulfur-containing amino acids [START_REF] Summer | Role of phages in the pathogenesis of Burkholderia, or 'Where are the toxin genes in Burkholderia phages?[END_REF] ; enzymes involved in nucleotide metabolism, including dUTPase, thymidylate synthase X and nucleoside pyrophosphohydrolase MazG, which might function in disarming antiviral systems triggered by nucleotidebased alarmones, such as ppGpp (for more details see Supplementary text).

Discussion

Here we describe three previously undetected, distinct groups of viruses associated with asgardarchaea of the lineages Lokiarchaeia and Thorarchaeia. Each group was identified in marine sediment samples from geographically remote sites (Fig. 6), suggesting a wide distribution of these viruses in asgardarchaea inhabited ecosystems. In addition, we recovered seven CRISPRtargeted MGEs associated with Lokiarchaeia, Thorarchaeia and Heimdallarchaeia that might represent distinct viruses with structural and morphogenetic proteins unrelated to those of any known viruses or, perhaps, more likely, plasmids. Although verdandiviruses, skuldviruses and wyrdviruses, in all likelihood, do not comprise the complete Asgard virome, they provide important insights into the diversity and evolution of the Asgard viruses. All three virus groups are sufficiently distinct from previously characterized viruses to be considered as founding representatives of three previously undescribed families. Wyrdviruses appear to be evolutionarily related to spindle-shaped viruses and thus belong to one of the archaea-specific groups of viruses [START_REF] Prangishvili | The enigmatic archaeal virosphere[END_REF] , not known in bacteria or eukaryotes. In archaea, spindle-shaped viruses are widely distributed and infect hyperthermophilic, halophilic and ammoniaoxidizing hosts from different phyla [START_REF] Krupovic | Unification of the globally distributed spindle-shaped viruses of the Archaea[END_REF][START_REF] Kim | Spindle-shaped viruses infect marine ammonia-oxidizing thaumarchaea[END_REF] . Thus, wyrdviruses might further expand the reach of spindleshaped viruses to asgardarchaea, supporting the notion that this group of viruses was associated with the last archaeal common ancestor (LACA) [START_REF] Krupovic | The LUCA and its complex virome[END_REF] . By contrast, verdandiviruses and skuldviruses encode HK97-like and DJR MCPs, respectively, and accordingly, at the highest taxonomic level, belong to the realms Duplodnaviria and Varidnaviria. Viruses of both realms have deep evolutionary origins and were proposed to have been present in both LUCA and LACA [START_REF] Krupovic | The LUCA and its complex virome[END_REF] . The current work further supports this inference. Although members of both Duplodnaviria and Varidnaviria also infect eukaryotes, analyses of the verdandivirus and skuldvirus genome and protein sequences unequivocally show that they are more closely, even if distantly, related to their respective prokaryotic relatives. Thus, no putative direct ancestors of eukaryotic viruses were detected. Further exploration of the asgardarchaeal virome is needed to determine whether any of the virus groups associated with extant eukaryotes originate from Asgard viruses.

All prokaryotic members of the realms Duplodnaviria and Varidnaviria are lytic viruses, which are released from the host cells by lysis (although some alternate lysis with lysogeny) [START_REF] Cahill | Phage Lysis: Multiple Genes for Multiple Barriers[END_REF][START_REF] Snyder | Lytic viruses infecting organisms from the three domains of life[END_REF][START_REF] Krupovic | A novel lysis system in PM2, a lipid-containing marine double-stranded DNA bacteriophage[END_REF] . Thus, verdandiviruses and skuldviruses are also likely to kill their hosts at the end of the infection cycle, thereby promoting the turnover of asgardarchaea and nutrient cycling in deep-sea ecosystems. This possibility is consistent with previous results showing that viruses in deep-sea sediments lyse archaea faster compared to bacteria [START_REF] Danovaro | Virus-mediated archaeal hecatomb in the deep seafloor[END_REF] . By contrast, the mechanism of virion release employed by spindleshaped viruses does not involve cell lysis, with virions continuously released from chronically infected cells [START_REF] Kim | Spindle-shaped viruses infect marine ammonia-oxidizing thaumarchaea[END_REF][START_REF] Quemin | Eukaryotic-like virus budding in Archaea[END_REF] . Infection of marine Nitrososphaeria with spindle-shaped virus NSV1resulted in inhibition of the host growth and was accompanied by severe reduction in the rate of ammonia oxidation and nitrite reduction [START_REF] Kim | Spindle-shaped viruses infect marine ammonia-oxidizing thaumarchaea[END_REF] . Thus, infection dynamics and the impact of wyrdviruses is likely to be quite different from those of verdandiviruses and skuldviruses. Finally, some of the asgardarchaeal viruses carry auxiliary metabolic genes, such as the gene encoding PAPS reductase, which might boost the metabolism of infected cells.

The present work is accompanied by two other studies, by Tamarit et al [START_REF] Tamarit | A closed Candidatus Odinarchaeum chromosome exposes Asgard archaeal viruses[END_REF] and Rambo et al [START_REF] Rambo | Unique viruses that infect Archaea related to eukaryotes[END_REF] , respectively, describing the identification of other asgardarchaeal viruses. Rambo et al describe several distinct groups of viruses, all members of the class Caudoviricetes. The complete genomes of these viruses are considerably larger than those of verdandiviruses described here and have distinct gene contents, justifying their placements into separate families. The study by Tamarit et al describes two viruses, Huginnvirus and Muninnvirus, related to icosahedral and spindle-shaped viruses, respectively. Huginnvirus is only distantly related to skuldviruses described here, with the two groups of viruses forming disconnected clusters in the MCP network (Fig. 4b). Muninnvirus is distantly related to wyrdviruses associated with Lokiarchaeia from our study, but infects a host from the asgardarchaeal class Odinarchaeia. Thus, viruses described in the three studies complement each other by representing distinct virus groups. Collectively, these findings provide valuable insights into the virome of asgardarchaea and open the door for understanding virus-host interactions in the deep-sea ecosystems. Undoubtedly, many more asgardarchaeal virus groups remain to be discovered, which should clarify the contribution of these viruses to the evolution of the extant eukaryotic virome.

Methods

Site description and sampling

A total of 365 m of sediment cores were recovered from Hole C9001 C of Site C9001 (water depth of 1,180 m) located at the forearc basin off the Shimokita Peninsula, Japan (41˚10.638N, 142˚12.081E) by the drilling vessel Chikyu during JAMSTEC CK06-06 cruise in 2006. Coring procedure, subsampling for the molecular analyses, profiles of lithology, age model, porewater inorganic chemistry, organic chemistry and cell abundance, summary of the molecular microbiology in sediments at site C9001 were reported previously [START_REF] Nunoura | Variance and potential niche separation of microbial communities in subseafloor sediments off Shimokita Peninsula, Japan[END_REF][START_REF] Kaneko | Insights into the methanogenic population and potential in subsurface marine sediments based on coenzyme F430 as a function-specific compound analysis[END_REF] (and references therein). Subsampled whole round cores (WRCs) for microbiology were stored at -80˚C.

Sample descriptions

A total of 12 sediment samples at depths of 0.9, 9.3, 18.5, 30.8, 48.3, 59.5, 68.8, 87.7, 116.4, 154.3, 254.7 and 363.3 mbsf were used in this study. These representatives were chosen based on porewater chemical profiles, lithostratigraphic properties, molecular biology data on the core sediments and F430 contents as follows. Note that 10 samples at depths of 0.9, 9.3, 18.5, 30.8, 48.3, 59.5, 116.4, 154.3, 254.3 and 363.3 mbsf were previously analyzed by SSU rRNA gene tag sequencing with a 454 FLX Titanium sequencer, and details have been reported in ref [START_REF] Nunoura | Variance and potential niche separation of microbial communities in subseafloor sediments off Shimokita Peninsula, Japan[END_REF] . At 0.9 mbsf, the uppermost section of the core column was chosen. At 9.3 mbsf, the region just beneath the SMTZ was chosen. At 18.5 mbsf, highest relative abundance of Lokiarchaeia was found in the previous SSU rRNA gene tag sequencing. At 48.3 mbsf, relatively higher abundance of SAGMEG in the archaeal community was observed. At 59.5 mbsf predominance of a lineage in Nanoarchaeia (formerly Woesearchaeota) was observed. For the sediment, at depth of 68.8 mbsf, the sample harbored anomalously high F430 concentrations, and the sample from a depth of 87.7 mbsf was used as a reference. Sediment at 116.4 mbsf consisted of ash/pumice, whereas other samples used in this study were pelagic clay sediments, and predominance of Bathyarchaeia was observed. Samples from 154.3, 254.3 and 363.3 mbsf were selected in 100 m depth intervals from the bottom of this drilling hole [START_REF] Nunoura | Variance and potential niche separation of microbial communities in subseafloor sediments off Shimokita Peninsula, Japan[END_REF][START_REF] Kaneko | Insights into the methanogenic population and potential in subsurface marine sediments based on coenzyme F430 as a function-specific compound analysis[END_REF] .

Shotgun metagenomics and SSU rRNA gene tag sequencing

DNA extraction and shotgun metagenome library construction were described in ref [START_REF] Hirai | Library construction from subnanogram DNA for pelagic sea water and deep-sea sediments[END_REF] . Briefly, total environmental DNA was extracted from approximately 5 g of sediment subsampled from inner part of WRC using DNeasy PowerMax Soil Kit (Qiagen) with a minor modification [START_REF] Hiraoka | Microbial community and geochemical analyses of trans-trench sediments for understanding the roles of hadal environments[END_REF] . Then, further purification was performed, NucleoSpin gDNA Clean-up (MACHERY-NAGEL, Germany). The purified DNA was used for Illumina sequencing library construction using a KAPA Hyper Prep Kit (for Illumina) (KAPA Biosystems, Wilmington, MA, USA). Sequencing was performed on an Illumina HiSeq 2500 platform (San Diego, CA, USA) and 250-bp paired-end reads were generated.

Assembly, binning, and Asgardarchaeota phylogeny

Contigs from each sample were assembled using MetaSpades v0.7.12-r1039 [START_REF] Nurk | metaSPAdes: a new versatile metagenomic assembler[END_REF] and binned with UniteM (https://github.com/dparks1134/unitem). Metagenome-assembled genome (MAG) sets were generated after a dereplication of bins using DAS_Tool v1.1.2 [START_REF] Sieber | Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy[END_REF] and quality check using CheckM [START_REF] Parks | CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes[END_REF] . MAGs with an estimated quality (completeness -4*contamination) of less than 30% were excluded in the downstream analysis. Taxonomic assignments of all MAGs were performed using the 'classify' function in GTDBtk [START_REF] Chaumeil | Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF] .

The phylogenetic analysis included 20 Asgardarchaeota MAGs, together with 255 published Asgardarchaeota and 64 non-Asgardarchaeota archaeal genomes. A marker set consisting of 53 ribosomal proteins of the 239 genomes were identified and independently aligned using the 'identify' and 'align' functions in GTDBtk [START_REF] Chaumeil | Tk: a toolkit to classify genomes with the Genome Taxonomy Database[END_REF] . The individual multiple sequence alignments were then concatenated and trimmed in GTDBtk using 'trim_msa' (--min_perc_aa 0.4).

Maximum likelihood phylogenies of Asgardarchaeota MAGs were initially estimated by FastTree v2.1.11 [START_REF] Price | FastTree 2-approximately maximum-likelihood trees for large alignments[END_REF] with default settings, and subsequently inferred using IQ-Tree v1.6.984 [START_REF] Nguyen | IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies[END_REF] under the LG+C10+F+G+PMSF model with 100 bootstraps. The final consensus tree was visualized and beautified in iTOL [START_REF] Letunic | Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation[END_REF] .

Assembly and analysis of viral contigs

Potential viral and MGE contigs were assembled from metagenomic reads by MetaViralSPAdes pipeline with default parameters [START_REF] Antipov | SPAdes: assembly of viruses from metagenomic data[END_REF] . Direct and inverted terminal repeats were identified by BLASTN [START_REF] Altschul | Basic local alignment search tool[END_REF] . Open reading frames were identified with Prokka 79 and annotated using HHsearch [START_REF] Steinegger | HH-suite3 for fast remote homology detection and deep protein annotation[END_REF] against Pfam, PDB, SCOPe, CDD and viral protein sequence databases. Minimum information about uncultured virus genomes (MIUViG) [START_REF] Roux | Minimum Information about an Uncultivated Virus Genome (MIUViG)[END_REF] assembled in the course of this work is provided in Table S7. Read depth along the assembled viral genomes is shown in Fig. S4. To identify similar contigs in public databases we searched sequences of major capsid proteins in GenBank and JGI databases (BLASTP, E-value cutoff of 1e-05, 70% query coverage). Genomes of assembled viral genomes were compared and visualized using EasyFig [START_REF] Sullivan | Easyfig: a genome comparison visualizer[END_REF] with the tBLASTx option. Network analysis of viral genomes was performed using vConTACT v2.0.9.19 with default parameters against Viral RefSeq v201 reference database [START_REF] Jang | Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks[END_REF] . The virus network was visualized with Cytoscape [START_REF] Shannon | Cytoscape: a software environment for integrated models of biomolecular interaction networks[END_REF] .

Collection of the CRISPR spacer dataset CRISPR arrays were detected in metagenomic contigs and 255 published Asgardarchaeota MAGs using minced v0.4.2 [START_REF] Bland | CRISPR recognition tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats[END_REF] and CRISPRDetect [START_REF] Biswas | CRISPRDetect: A flexible algorithm to define CRISPR arrays[END_REF] . CRISPR arrays from metagenomic contigs were assigned to "Asgard" and "non-Asgard" groups based on CRISPR repeat similarity to previously characterized Asgard CRISPR repeats with 90% identity cutoff over full length of repeat [START_REF] Makarova | Unprecedented diversity of unique CRISPR-Cas-related systems and Cas1 homologs in Asgard archaea[END_REF] . CRISPR repeat sequences from metagenomic contigs and from Asgard MAGs were then clustered together using all-against-all BLASTN search (E-value cutoff of 1e-05, 90% identity, word size 7) and the result of clustering was visualized in Cytoscape [START_REF] Shannon | Cytoscape: a software environment for integrated models of biomolecular interaction networks[END_REF] . Consensus sequences for the 9 major clusters of CRISPR repeats were constructed using python package Logomaker [START_REF] Tareen | Logomaker: beautiful sequence logos in Python[END_REF] .

Assignment of CRISPR arrays to Asgardarchaeota

To assemble the CRISPR spacer database, we relied on two categories of CRISPR loci: 1) "reference" sequences of manually curated Asgard CRISPR loci from Makarova et al [START_REF] Makarova | Unprecedented diversity of unique CRISPR-Cas-related systems and Cas1 homologs in Asgard archaea[END_REF] and CRISPR loci from asgardarchaeal MAGs; 2) "metagenomic" CRISPR loci from contigs originating from the Shimokita Peninsula subseafloor sediments. CRISPR loci from the latter category were assigned to asgardarchaea if the identity of CRISPR repeat to the reference asgardarchaeal CRISPRs from the former category was above 90% and protein sequences encoded on these CRISPR-containing contigs (when present) had best BLASTP hit to asgardarchaeal proteins. All "reference" contigs were downloaded from GenBank without annotation. We used prodigal and CRISPR-Cas++ to identify cas genes in the contigs with CRISPR arrays. Protein sequences were compared to the nr database with BLASTP to confirm Asgard assignment of the contig with CRISPR.

Verdandiviruses were targeted by spacers from 5 "reference" and 4 "metagenomic" CRISPR loci (Extended Data 1). The length of "reference" contigs varied from 3 to 126 kbp. Five reference contigs and one metagenomic contig contained cas genes, with the most conserved Cas protein (Cas1) being assigned to asgardarchaea (Lokiarachaeia, Helarchaeia) by the best BLASTP hit with 72-74% identity. Skuldviruses were targeted by spacers from 3 "reference" and 3 "metagenomic" CRISPR loci, whereas wyrdviruses were targeted by spacers from 2 "reference" and 3 "metagenomic" CRISPR loci (Extended Data 1). CRISPR repeats of "metagenomic" contigs targeting the three groups of viruses were 97% identical to the CRISPR repeats from the "reference" category [START_REF] Makarova | Unprecedented diversity of unique CRISPR-Cas-related systems and Cas1 homologs in Asgard archaea[END_REF] .

Asgardarchaeal CRISPR repeats

Predicted asgardarchaeal CRISPR arrays contained distinct repeats which could be clustered into 9 groups with 90% identity of sequences within groups (Fig. 2A). Comparison of the asgardarchaeal CRISPR repeats to those in public RepeatTyper database produced significant results only for group 9 repeat, which was identified as belonging to CRISPR-Cas type I-E. The closest repeat to group 9 was from Thermobaculum terrenum, with 2 mismatches (27/29). Repeats from groups 4 partially matched to Desulfosarcina (29/37). Other repeat groups showed no matches in CRISPR-Cas++ database (https://crisprcas.i2bc.paris-saclay.fr/).

Structural modeling and network analysis of the major capsid proteins

Structural modeling of the representative verdnadivirus and skuldvirus major capsid proteins was performed with RoseTTAFold [START_REF] Baek | Accurate prediction of protein structures and interactions using a three-track neural network[END_REF] . The MCPs of skuldviruses were compared to the DJR MCPs of other known prokaryotic viruses using CLANS [START_REF] Frickey | CLANS: a Java application for visualizing protein families based on pairwise similarity[END_REF] , an implementation of the Fruchterman-Reingold force-directed layout algorithm, which treats protein sequences as point masses in a virtual multidimensional space, in which they attract or repel each other based on the strength of their pairwise similarities (CLANS p-values). The reference dataset of DJR MCP was obtained from Ref [START_REF] Yutin | Vast diversity of prokaryotic virus genomes encoding double jelly-roll major capsid proteins uncovered by genomic and metagenomic sequence analysis[END_REF] . Sequences were clustered using CLANS with BLASTP option (E-value of 1e-04) [START_REF] Frickey | CLANS: a Java application for visualizing protein families based on pairwise similarity[END_REF] .

Phylogenetic analysis of viral proteins

Sequences were aligned using MAFFT in 'Auto' mode 88 . For phylogenetic analysis, uninformative positions we removed using TrimAl with gap threshold of 0.2 for the verdandiviral MCPs and gappyout option for Topo mini-A [START_REF] Capella-Gutierrez | trimAl: a tool for automated alignment trimming in largescale phylogenetic analyses[END_REF] . The final alignments contained 323 and 277 positions, respectively. The maximum likelihood trees was inferred using IQ-TREE v2 [START_REF] Nguyen | IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies[END_REF] . The best-fitting substitution models were selected by IQ-TREE and were LG+G4 and LG+R5 for verdandiviral MCPs and Topo mini-A, respectively. The trees were visualized with iTOL [START_REF] Letunic | Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation[END_REF] . Phylogenetic trees and underlying alignments in editable format are provided in Supplementary data 2.

CRISPR-based virus-host assignments

Spacer sequences from asgardarchaeal CRISPR arrays were matched to metagenomic contigs and published Asgard MAGs (BLASTN, E-value 1e-05, 90% identity, word size 7), and viral genomes available at IGV database (default parameters) at https://img.jgi.doe.gov/cgibin/m/main.cgi?section=WorkspaceBlast&page=viralf orm. To assess the false positive rate of BLASTN, we used a control set of viral contigs from human metagenomes (~400,000 sequences) [START_REF] Nayfach | Metagenomic compendium of 189,680 DNA viruses from the human gut microbiome[END_REF][START_REF] Camarillo-Guerrero | Massive expansion of human gut bacteriophage diversity[END_REF][START_REF] Gregory | The Gut Virome Database Reveals Age-Dependent Patterns of Virome Diversity in the Human Gut[END_REF][START_REF] Shkoporov | The Human Gut Virome Is Highly Diverse, Stable, and Individual Specific[END_REF] . Seven spacers out of 2532 (FPR = 0.00276) were matched to a control dataset by BLASTN with the same parameters (E-value 1e-05, 90% identity, word size 7). For each spacer we calculated the difference between identity of best match in the test and control datasets. Spacers with less than 10% identity difference (n=5) were removed as potential low-complexity spacers. SpacePHARER [START_REF] Zhang | SpacePHARER: Sensitive identification of phages from CRISPR spacers in prokaryotic hosts[END_REF] with FDR rate of < 0.001 was used for sensitive search of protospacers with lower nucleotide identity to support the BLASTN results. CRISPRHost (https://github.com/davidchyou/CRISPRHost) and CRISPR Spacer Database and Exploration Tool [START_REF] Dion | Streamlining CRISPR spacer-based bacterial host predictions to decipher the viral dark matter[END_REF] were used to match large collections of prokaryotic spacers to identified Asgard MGE sequences.

Kmer-based virus-host assignments

WIsH [START_REF] Galiez | WIsH: who is the host? Predicting prokaryotic hosts from metagenomic phage contigs[END_REF] and PHIST [START_REF] Zielezinski | PHIST: fast and accurate prediction of prokaryotic hosts from metagenomic viral sequences[END_REF] S8). For the virus dataset, we used MGE sequences targeted by Asgard spacers. Viral contigs from human metagenomes were used as a negative dataset to calculate null parameters for models of hosts for WIsH.

WIsH confirmed asgardarchaeal hosts for all MGE sequences targeted by asgardarchaeal spacers with a Pvalue ranging from 1.18e-06 for WyrdV1 to 1.32e-01 for VerdaV2 (Table S5). In the 25-mer-based PHIST analysis, we only considered predictions based on >10 kmers. Using these parameters, hosts were predicted for 17 out of 28 (60%) contigs. Of these, 11 (65%) contigs, representing all groups of viruses and MGEs described in this work, were predicted to be associated with asgardarchaea. However, the remaining 6, all verdandiviruses, were affiliated to Thermoplasmatota MAG 2H_mb2_bin16 assembled from Shimokita peninsula dataset. We note that the latter prediction likely results from the inclusion of a small (~2 kbp) verdandivirus-like contig into Thermoplasmatota MAG 2H_mb2_bin16, which is likely a binning artefact, because full-length verdandivirus contig was assigned to Lokiarachaeia MAG. Indeed, we could not confirm Thermoplasmatota assignment as a verdandivirus host with CRISPR spacer analysis.

To further verify the validity of our CRISPR matches, we checked the predicted asgardarchaeal viruses and MGEs for the presence of non-Asgard protospacers using large spacer collections of CRISPRHost and CRISPR Spacer Database and Exploration Tool (CRISPR_SDET). CRISPRHost did not find any protospacers with the default parameters. CRISPR_SDET search was performed with 90% identity threshold. Two protospacers were found: verdandivirus VerdaV4 was assigned to Floccifex porci, a Firmicutes bacterium from pig gut metagenome; two mobile elements from the "Other" group, JGI-127 and JGI-148, were assigned to Treponema species, a pathogenic bacterium of humans and other mammals. Given that neither of these bacteria reside in deep-sea sediments, the two spacers are likely to represent false positives.

--CCCCCC----cHHHHHHHHC--- Q ss_pred CCCCCCCCCCchhhceecchh---cCCCCCCCceEEEEEECCC-----------CeEEEEeccCcEecCCCCCCceeece Q VerdaV1 224 GEKGTEPFIPDINQITETDAL---YNGTLSTATQAFLLWKDDI-----------NCNYIAEAYPIHRAGIPNKEFEGDID 289 (318) Q Consensus 224 ~~~~~~~~~~~~~~i~~~~~~---~~~~~~~~~d~~l~~~~~~-----------
----------~~t~a~I~~I~v~~NG~~i~~~~~~-----------~~L~~~n~y 71 (269) T P15794 14 AAGNSCSIKLPIGQTYEVIDLRYS-----------GVTPSQIKNVRVELDGRLLSTYKTL-----------NDLILENTR 71 (269) T ss_pred CCCCEEEEEcCCCCeeEEEEEEEc-----------CCCHHHcCeEEEEECCEEEEEeCCH-----------HHHHHHHHH Q ss_pred hcccCCccceeEEEcCCccCCC-------------------CeEEEEEEecceeeecCCCCceeeeceEEEEEEeCCCCe Q SkuldV1 94 RNKVADADEYFEIDFPKAIGRG-------------------HNAYIDFRFNTIANMNDGDRTTYTGATIDIMVEVGTPGR 154 (277) Q Consensus 94 ~~~VA~~d~y~~I~FP~aip~g-------------------

FiguresFigure 1 |

 1 Figures

Figure 2 |

 2 Figure 2 | Description of the Asgardarchaeota CRISPR spacer dataset. a, Similarity of CRISPR repeats from metagenomic data (Bermuda) and CRISPR repeats from Asgardarchaeota MAGs (red). Unique CRISPR repeat sequences are shown as nodes in the network. The diameter of the node is proportional to the number of spacers associated with the repeat sequence in the dataset. Identical CRISPR repeats from metagenomic data and from Asgard MAGs are connected with solid lines. Dashed and dotted lines connect CRISPR repeat sequences with 95-99% and 90-95% identities, respectively. Consensus sequences for the nine major clusters are shown on the right. b, The source of the Asgardarchaeota CRISPR spacers. The number of spacers in the dataset originating from different geographical sites is indicated on the pie chart. c, Taxonomic distribution of Asgardarchaeota MAGs with CRISPR arrays for different isolation sites. The size of the circle is proportional to the number of spacers in the dataset.

Figure 3 |

 3 Figure 3 | Diversity of verdandiviruses. a, Genome maps of verdandiviruses. Homologous genes are shown using the same colors and the key is provided at the bottom of the panel. Also shown is the deduced schematic organization of the verdandivirus virion with colors marching those of the genes encoding the corresponding proteins. Genes encoding putative DNA-binding proteins with Zn-binding and helix-turn-helix domains are colored in black and grey, respectively. Colored circles indicate the positions of protospacers. Grey shading connects genes displaying sequence similarity at the protein level, with the percent of sequence identity depicted with different shades of grey (see scale at the bottom). Asterisks denote complete genomes assembled as circular contigs. Abbreviations: PAPSR, phosphoadenosine phosphosulfate reductase; TMP, tail tape measure protein; MTP, major tail protein; MCP, major capsid protein; TerL, large subunit of the terminase. b, Comparison of the structural model of the major capsid protein of verdnadivirus AsTV-10H2 with the corresponding structures of siphoviruses TW1 and HK97. The models are colored according to the secondary structure: α-helices, dark blue; β-strands, light blue. c, Maximum likelihood phylogeny of the major capsid proteins encoded by verdandiviruses. Taxa are colored based on the source of origin (key at the bottom of the figure), with those for which genomic contigs are shown in panel A shown in bold. The tree was constructed using the automatic optimal model selection (LG+G4) and is mid-point rooted. The scale bar represents the number of substitution per site. Circles at the nodes denote aLRT SH-like branch support values larger than 90%.

Figure 4 |

 4 Figure 4 | Diversity of skuldviruses. a, Genome maps of skuldviruses and PM2 virus. Homologous genes are shown using the same colors and the key is provided at the bottom of the panel. Also shown is the deduced schematic organization of the skuldvirus virion with colors marching those of the genes encoding the corresponding proteins. Colored circles indicate the positions of protospacers. Grey shading connects genes displaying sequence similarity at the protein level, with the percent of sequence identity depicted with different shades of grey (see scale on the right). Asterisks denote complete genomes assembled as circular contigs. Abbreviations: RCRE, rolling circle replication endonuclease; DJR-MCP, double jelly-roll major capsid protein; HTH, helix-turn-helix. Genome map of corticovirus PM2 is shown for comparison. b, Sequence similarity network of prokaryotic virus DJR MCPs. Protein sequences were clustered by the pairwise sequence similarity using CLANS. Lines connect sequences with CLANS P-value ≤ 1e-04. CLANS uses p-values of BLASTP comparisons calculated from Poisson distribution of high scoring segment pairs. Different previously defined groups 42 of DJR MCP are shown as clouds of differentially colored circles, with the key provided on the right. Note that the Odin group has been named as such previously because some of the MCPs in this cluster originated from the Odinarchaeia bin 42 . The position of Huginnvirus described by Tamarit et al 65 is indicated. PRD1, Toil, and Bam35 subgroups are named after the corresponding members of the family Tectiviridae. Skuldviruses are highlighted within a yellow circle. When available, MCP structures of viruses representing each group are shown next to the corresponding cluster (PDB accession numbers are given in the parenthesis). Skuldvirus cluster is represented by a structural model of the SkuldV1 MCP. The models are colored according to the secondary structure: α-helices, dark blue; β-strands, light blue.

Figure 5 |

 5 Figure 5 | Diversity of wyrdviruses. Genome maps of wyrdviruses, fusellovirus SSV1 and halspivirus His1. Homologous genes are shown using the same colors and the key is provided at the bottom of the panel. Also shown is the deduced schematic organization of the skuldvirus virion with colors marching those of the genes encoding the corresponding proteins. Colored circles indicate the positions of protospacers. Genes encoding putative DNA-binding proteins with Zn-binding and helix-turn-helix domains are colored in black and grey, respectively. Grey shading connects genes displaying sequence similarity at the protein level, with the percent of sequence identity depicted with different shades of grey (see scale on the right). Asterisks denote complete genomes assembled as circular contigs or linear contigs with terminal inverted repeats. The topology of each genome is shown next to the corresponding name: circle for circular genomes, lines for linear genomes. Abbreviations: ThyX, thymidylate synthase X; NMAD, nucleotide modification associated domain 1 protein; O-MTase, carbohydrate-specific methyltransferase; TFB, transcription initiation factor B; ASCH, ASC-1 homology domain; RCRE, rolling circle replication endonuclease; MCP, major capsid protein, pPolB, protein-primed family B DNA polymerase. Genome maps of SSV1 and His1 viruses are shown for comparison.

Figure 6 |

 6 Figure 6 | Asgardarchaeal viruses and MGEs. a, Geographical distribution of asgardarchaeal viruses and MGEs. Filled circles next to geographical locations signify the presence of the corresponding virus groups in sediment samples from that location. b, The network-based analysis of shared protein clusters (PCs) among asgardarchaeal viruses and the prokaryotic dsDNA viruses. The nodes represent viral genomes, and the edges represent the strength of connectivity between each genome based on shared PCs. Nodes representing genomes of the three groups of asgardarchaeal viruses are in shown in red and the three groups are circled with yellow background. Nodes corresponding to other bacterial and archaeal viruses are shown in blue and orange, respectively.

Figure S1 .

 S1 photolyase TFB PCNA

  T Consensus 152 ~~~~~~~~~~--~~El~~a~~~g~-~l~~~k~~aa~~~~~~~~n~i~f~G~~~~~~~~~~GLlN~--------p~l~~~~ 220 (382) T A0A0U5AF03 152 VRGELGMMVG--TLEEGRASAIRL-NSAETKRQQAAIGLEIFRNAIGFYGWQSGLGNRTYGFLND--------PNLPPFQ 220 (382) T ss_pred EEEEEEeEec--hHHHHHHHhcCC-CHHHHHHHHHHHHHHHHHHhhEeeeecCCCCCceeecccC--------CCCCccC Q ss_pred c---Cccc--chHHHHHHHHHHHHHH--HHCCCCCC----CEEEEChhHHHHHhcccCCCCCCcHHHHHHHHHHhcCCcc Q VerdaV1 155 T---LTWT--NNLQFSLEMEIARGLL--RAAHIMPP----YKLWMTPGIRPTLRANVNATTGVSDWKLFQQDWMNSGVIS 223 (318) Q Consensus 155 ~---~~W~--t~~~i~~dv~~ai~~L--~~~g~~~p----~~L~L~p~~y~~L~~~~~~~t~~~~~~~i~~~i~~~~~~~ 223 (318) . .+|. ++.++++||..++.+| .+.++++| ++|+||++.|..|.+ .+..+. +++++|+++. T Consensus 221 ~~~~~~W~~~T~~eI~~dv~~~~~~l~~~s~g~~~p~~~~~tL~lp~~~~~~L~~--~~~~~~----tvl~~Lk~~~---291 (382) T A0A0U5AF03 221 TPPSQGWSTADWAGIIGDIREAVRQLRIQSQDQIDPKAEKITLALATSKVDYLSV--TTPYGI----SVSDWIEQTY---291 (382) T ss_pred CCCCCCcccCCHHHHHHHHHHHHHHHHHHcCCCCCCCCCceEEEEeHHHHHHhcc

Figure S3 .

 S3 Figure S3. HHsearch profile-profile comparisons between the putative major capsid protein of skuldvirus SkuldV1 and the double jelly-roll major capsid proteins of (a) corticovirus PM2, (b) turrivirus STIV, and (c) tectivirus PRD1. H(h), α-helix; E(e), β-strand; C(c), coil.

  ++++.++|.+||.+|++.++..+.+|+|++ +... .|+.....++.++..+.+ +++......+.+ ......++

	a b	Supplementary figures
	>P17312 TERL_BPT4 Terminase, large subunit OS=Enterobacteria phage T4 OX=10665 GN=17 PE=1 SV=1 >A0A0U5AF03 CAPSD_BPK22 Major capsid protein OS=Pseudomonas phage KPP22 OX=1772250 PE=1 SV=1
	Probab=100.00 E-value=4.1e-34 Score=301.28 Aligned_cols=403 Identities=15% Similarity=0.129 Sum_probs=304.0 Template_Neff=10.300 Probab=99.97 E-value=3.5e-29 Score=244.70 Aligned_cols=275 Identities=11% Similarity=0.022 Sum_probs=0.0 Template_Neff=7.800
	Q ss_pred Q ss_pred	HHHHHhcCCHHHHHHHHHhhhhhccEEeecccCCCceeeeceeccCCCHHHHHHHHHHhhcCeEEEEeCCCCCHHHHHHH CcccCCCHHHHHHHHHHHHHhhcchhccccCCCCCCCC-ccceEEEeeeeeeceecc--ccCCcccccccc-cceEEEEe
	Q VerdaV1 Q VerdaV1	95 RILQMGTNDARILNTAISFLDKTNQFIVKEESENKGFVDYQVITEKLTDKQLNIFNAMIREGWVSLLGCRKTGKTFLISS 174 (521) 2 VEIHGVSERQWKGIDTQVAQLMREPIVYTRLPSGMQIG-KGKNKAEYFQATDIFYVN--EGNRFSYEDKNT-GARKIRDA 77 (318)
	Q Consensus Q Consensus	95 ~~~~~~~~d~~~~~~~~~f~~~~~~~~~~~~~~~~~~~~~~~~~~~l~~~Q~~~~~~~~~~~~~~~~~~rg~GKT~~~~~ 174 (521) 2 ~~~~~l~~~~w~~Id~~v~~~~~~~L~ar~l~p~v~~~-~G~~~~~~~~~~d~~~~~--~g~~~~~~~v~~-~~~~~~~v 77 (318)
	+...+|+.|+.+ 108 ~~~~~~~~d~~~------f~~~~~~----i~~~~~~-----~~~~~~~~~q~~~~~~~~~~~~~i~~~~r~~GKT~~~~~ 172 (610) |++.|+. +.++..+ ..++.+.++|+++++.+...+.+++.+|||+|||++++. ...T Consensus T Consensus 73 ~~~~~ip~~~l~~id~~vi~~~~~~~~~~~li~-v~~~g~w~~~~~~~~~~e~~G~a~~~~d~~d~p~~~~~~~~~~~~v 151 (382)
	T P17312 T A0A0U5AF03	108 EEWKKCRDDIVY------FAETYCA----ITHIDYG-----VIKVQLRDYQRDMLKIMSSKRMTVCNLSRQLGKTTVVAI 172 (610) 73 TPSIPTPIQFLQTWLPGLVKVMTAARKIDEIIG-IDTVGSWEDQEIVQGIVEPAGTAVEYGDHTNIPLTSWNANFERRTI 151 (382)
	T ss_pred T ss_pred	HHHHHHHcCHHH------HHHhCcE----EEeCCCC-----eeccCCCHHHHHHHHHHhhCCcEEEEeCchhcHHHHHHH CCCCchHHHHHHHhccchhccccccccHHHHcC-cccCCCceeEEEEEEEecCCceEEEecCCCCCceeeeEeeceeeee
	Confidence	334588999999	9999988	6555333	344589999999999887788899999999999999987
	Q ss_pred	EEEEEEecccccHHHHHHHHhcCCCCchHHHHHHHHHHHHHHHhCeEeecCC---ccCcccceecccCCCccCCCceeee
	Q ss_pred Q VerdaV1	HHHHHh-hCCCCEEEEEeCCHHHHHHHHHHHHHHHHhCCcc---ceecCCCCEEEeCCCCEEEEEECCCccccCCcccEE 78 IITYLTLPIHIDEKDIDASSSEGITPLLVQMEVECRAKMQEKIQKIILHGSA---HTGGRGICTFQQDGDVVEQTYAFEA 154 (318)
	Q VerdaV1 Q Consensus	175 AITYLG-SRKKLEIHVLSSKKDTAAHIITQVIGINAEHQFN---LLKRPAKELINFENGTRIKVHSNTLADTGTYEADIL 250 (521) 78 ~~i~~~f~i~~~~rel~as~~~g~~~ld~~~a~~A~r~vae~ed~lif~G~~---~~gi~GL~n~~~~~~~~~~g~~~~~ 154 (318)
	Q Consensus	175 ~~~~~~-~~~~~~i~~~s~t~~~a~~~~~~~~~~~~~~~~~---~~~~~~~~~i~~~~g~~i~~~~~~~~~~~G~~~~~i 250 (521) +.++..|.++ ++|++++++.|. +++.+++.+|++.+++++|+++|+|++ ..+++||+|+ ++.+...
			.+++.+ ..++..+++++++.++|.+++..+..++...+..	.....+...+.+.||+.|.+.+.+....+|.+++++
	T Consensus	173 ~~~~~~~~~~~~~i~i~s~~~~~a~~~~~~i~~~i~~~p~~~~~~~~~~~~~~i~~~ng~~i~~~~~~~~~~~G~~~~~i 252 (610)
	T P17312	173 FLAHFVCFNKDKAVGILAHKGSMSAEVLDRTKQAIELLPDFLQPGIVEWNKGSIELDNGSSIGAYASSPDAVRGNSFAMI 252 (610)
	T ss_pred	HHHHHHHhCCCCcEEEEeCChhhHHHHHHHHHHHHHhCCHHhcCCceecCCCeEEECCCCEEEEEeCCCccccccceeEE
	Confidence	777764 6788899999999999999999998888776521	123456677889999999887766666789999999
	Q ss_pred	EEeChhhCCH--HHHHHHHHHHhcCCCeEEEEEecCCCCChHHHHhccCC---CCceEEEecHHHcC-------CCCHH-
	Q VerdaV1	251 VIDEAQEVDE--LVWSKIIPQLASGRKMRVYIFGTAKAGTPFYNFWFGVN---PKFQKFELGEEDAT-------WVPKE-317 (521)
	Q Consensus	251 i~DE~~~~~~--~~~~~~~~~l~~~~~~~ii~~stp~~~~~~~~~~~~~~---~~~~~~~~~~~~~p-------~~~~~-317 (521)
			++||++.++. +.+..+.+++....+++++++|||.+.+++++.+....	.+|..+..+|...+	.++.+
	T Consensus	253 ~iDE~~~~~~~~~~~~~~~~~~~~~~~~~~i~~sTp~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 (610)
	T P17312	253 YIDECAFIPNFHDSWLAIQPVISSGRRSKIIITTTPNGLNHFYDIWTAAVEGKSGFEPYTAIWNSVKERLYNDEDIFDDG 332 (610)
	T ss_pred	EEechhhCCCHHHHHHHHHHhccCCCCcEEEEEeCCCcchHHHHHHHHHHcCCCCeEEEeeeHHHCcccccCChhcccCc
	Confidence	9999999885 78888888888655789999999998889999888753	33555555554332	12222
	Q ss_pred	--HHHHHHhhCCHHHHHHHhhCcccCcccceecHHHHHHHHH-h-------ccc-CCCccCceEEEEEEcCC--CCCeEE
	Q VerdaV1	318 --SWDAIKSLMSDRMIRQELKMEWVEPEGAFFRAEDVEVAFE-E-------YSE-GFTRDYLEIVCAVDFGQ--GHETTM 384 (521)
	Q Consensus	318 --~~~~~~~~~~~~~f~~e~~~~~~~~~~~~f~~~~~~~~~~-~-------~~~-~~~~~~~~~~~giD~a~--~~d~~~ 384 (521)
			...+.+..+++..|.++|+|.|...++.+|+.+++..+.. .	... ..+.+...+++|+|+|. ++|.++
	T Consensus	333 ~~~~~~~~~~~~~~~f~~e~~~~~~~~~~~~f~~~~l~~~~~~~~~~~~~~~~~~~~~~~~~~~~~g~D~A~g~~~D~ta 412 (610)
	T P17312	333 WQWSIQTINGSSLAQFRQEHTAAFEGTSGTLISGMKLAVMDFIEVTPDDHGFHQFKKPEPDRKYIATLDCSEGRGQDYHA 412 (610)
	T ss_pred	chhhHHHHcCCCHHHHHHHhHhccccCCCCcccHhHheeceeeeccCCCCCeeEeeCCCCCCcEEEEEECccCCCCCccE
	Confidence	2333445678999999999999998999999887654311 0	000 01234678899999964 456554
	Q ss_pred	-EEEEEeCCeEEEEEEEcCCCCCHHHHHHHHHHHHHHcC-ceEEEcCCcchHHHHHHHHH----cCCcce-----ecCC-
	Q VerdaV1	385 -GNLAYRKEQIYEIESWGMFNPTSDMILAKVKEYGDRYS-SLFIMEGSPLGGFVRRDVKD----LRFKFK-----TSNF-452 (521)
	Q Consensus	385 -~v~~~~~~~~~~~~~~~~~~~~~~~~~~~i~~~~~~~~-~~~~~e~~~~g~~~~~~l~~----~g~~v~-----~~~~-452 (521)
			+++...++..++++.+.....++..+.+.+..+...|+ ..+++|.++.|..+.+.|.+	.|+.+.	++..
	T Consensus	413 i~v~~~~~~~~~~v~~~~~~~~~~~~~~~~i~~~~~~y~~~~i~iE~~~~g~~~~~~l~~~l~~~~~~~~~~~~~g~~~~ 492 (610)
	T P17312	413 LHIIDVTDDVWEQVGVLHSNTISHLILPDIVMRYLVEYNECPVYIELNSTGVSVAKSLYMDLEYEGVICDSYTDLGMKQT 492 (610)
	T ss_pred	EEEEECCCCccEEEEEEecCCCCCchHHHHHHHHHHHhCCCCEEEEeCchHHHHHHHHHHhhCCCCceeccCCCccccCC
	Confidence	45555566667777777666788889999999998888 45567888777766666654	344433	1222
	Q ss_pred	cccHHHHHHHHHHHHHcCCCCCCcHHHHHHHHhccCC--------CCCcHHHHHHHHHHHHHHHhhhh
	Q VerdaV1	453 SVHKDKYWFSLNFLLNNHLIHLKTQKLKQQLLLYRGD--------KIDDDWVDMLLHAAYYYFNKYYK 512 (521)
	Q Consensus	453 ~~~k~~~i~~l~~~~~~g~i~~~~~~l~~el~~~~~~--------~~~dD~~DAl~~a~~~~~~~~~~ 512 (521)
			+.+|..++..+..++++|++.+++..+++||..|.+.	+.|||.+||+++|++.+......
	T Consensus	493 ~~~K~~~~~~l~~~i~~g~l~i~~~~li~El~~f~~~~~~~~~~~~~~dD~vdAl~~a~~~~~~~~~~ 560 (610)
	T P17312	493 KRTKAVGCSTLKDLIEKDKLIIHHRATIQEFRTFSEKGVSWAAEEGYHDDLVMSLVIFGWLSTQSKFI 560 (610)
	T ss_pred	cccHHHHHHHHHHHHHcCCCEeCcHHHHHHHHhheeCCCCcccccCCcHHHHHHHHHHHHHHcchhhH
	Confidence	5678999999999999999999999999999999543	36999999999999887655443

Results of the HHsearch analysis queried with the putative large terminase subunit (a) and the major capsid proteins (b) of verdandivirus VerdaV1

					~~~~i~~~~~~~~~~~~~~~~~~~i~ 289 (318)
		|.+. |..++++++.	+.+	+.++++++.+++	+++.+.+|++++.++.+.+++.|.++
	T Consensus	292 ------p~i~-I~~~pel~~a~~~g~~----g~~~~~l~~~~~~~~~~g~~~~~~~~~~~vp~~~~~~~~~~~~~~~~~~ 360 (382)
	T A0A0U5AF03	292 ------PKMR-IVSAPELSGVQMKAQE----PEDALVLFVEDVNAAVDGSTDGGSVFSQLVQSKFITLGVEKRAKSYVED 360 (382)
	T ss_pred	------CCCE-EEECHhhhcccccCCC----CccEEEEEECchhcccCCCCCcccceeeeecccceecccEeccceEEEe
	Q ss_pred	EEEeeecEEeecCCCceEEE
	Q VerdaV1	290 YALRWAGCFLPKNPKGAVYV 309 (318)
	Q Consensus	290 ~~~r~gGv~~~~~~~~~~~~ 309 (318)
		|..+++|+++ |.|..|++.
	T Consensus	361 ~~~~t~G~~i-~rP~ai~~~ 379 (382)
	T A0A0U5AF03	361 FSNGTAGALC-KRPWAVVRY 379 (382)
	T ss_pred	eeceeeeEEE-eccceehhh
	Figure S2. a
	>P15794 CAPSD_BPPM2 Major capsid protein P2 OS=Pseudoalteromonas phage PM2 OX=10661 GN=II PE=1 SV=2
	Probab=98.32 E-value=0.0012 Score=61.40 Aligned_cols=219 Identities=12% Similarity=0.056 Sum_probs=0.0 Template_Neff=8.200
	Q ss_pred	eeecCceeeecceeeccEEEEEecCCcccCcchhheeeccccceEEEEECCEEEEEE-ecccCccccchHHHHHHHHHHH
	Q SkuldV1	15 AESENKHVKIDNTFPIKKIVIIHNPGDFAGGSTGVLIANTILDNLRVFVHGKEVISL-IGDVDVDTAPFAIQLMREANKL	93 (277)
	Q Consensus	15 a~~~~~~~ti~~tf~ik~I~I~~~~ga~sGGatG~~VaN~a~~s~rv~~nGk~iI~~-dG~~~vd~~s~gi~lLRE~~~~	93 (277)
		+.+.+.+++|+.-.....|.+..+		.+...-++.|||.+||+.++.+ +|	+.|..+|++
	T Consensus	14 ~~g~~at~~lp~g~tY~~i~l~~t-

. H(h), α-helix; E(e), β-strand; C(c), coil.

Acknowledgements

We thank the crews, technical staff and shipboard scientists of the DV Chikyu for the operation and sampling during CK06-06 cruise in 2006. We are grateful to Miho Hirai and Yoshihiro Takaki for the library construction and sequencing of the subseafloor samples from off Shimokita. The work in the M.K. laboratory is supported by grants from the l'Agence Nationale de la Recherche (ANR-20-CE20-0009-02 and ANR-21-CE11-0001-01) and Ville de Paris (Emergence(s) project MEMREMA). S.M. was supported by the Metchnikov fellowship from Campus France and Russian Science Foundation grant 19-74-20130. N.Y. and E.V.K. are supported by the Intramural Research Program of the National Institutes of Health of the USA (National Library of Medicine). The work by C.R and J. S. is funded by the Australian Research Council (ARC) Future Fellow Award (FT170100213) awarded to CR. T.N. was partly supported by MEXT KAKENHI Grant Number JP19H05684 within JP19H05679 (Post-Koch Ecology) and 16H06429, 16K21723 and 16H06437 (NeoVirology).

Code Availability

No custom code was used.

Data availability

The raw reads as well as assembled virus and MGE genome sequences from the metagenomes described in this study are available at NCBI under BioProject PRJDB12054, BioSample accessions: SAMD00394285-SAMD00394296. Accession numbers of the 20 MAGs assembled in the course of this study are listed in Supplementary table 1.

Extended Data Figure 4 | Sequence alignment of the major capsid proteins of selected wyrdviruses, fusellovirus SSV1 and halspivirus His1. TMD, transmembrane domain.

Author Contributions Statement M.K. initiated the project and designed research. T.N. collected the samples, extracted and sequenced the DNA. J.S. and C.R. assembled, curated and analyzed the asgardarchaeal MAGs. S.M. assembled the asgardarchaeal CRISPR and viral datasets. S.M., N.Y., E.V.K. and M.K. analyzed the viral sequences. S.M. and M.K. wrote the manuscript with input from all authors.

Competing interests

The authors declare no competing interests.

Extended Data

Extended Data Figure 1 | Matches between asgardarchaeal CRISPR spacers and viruses. The figure is divided into three blocks (green, red and blue) corresponding to the three groups of asgardarchaeal viruses, namely, verdandiviruses, skuldviruses and wyrdviruses. CRISPR repeats and spacers are indicated as diamonds and boxes, respectively. Spacers matching asgardarchaeal viruses are shown in yellow and are connected to the names of targeted viruses with arrows. Thick vertical lines connect related repeats and the exact pairwise sequence identities are indicated.

SUPPLEMENTARY INFORMATION

Supplementary text

Enigmatic MGEs of asgardarchaea

Two circular contigs, 7H_11 and 8H_18, were nearly identical and targeted by identical spacers affiliated to Thorarchaeia (Tables S3 andS4), but were assembled from metagenomes originating from samples collected at different depths (59.5 and 68.8 mbsf, respectively). Notably, 7H_42 discovered in our samples from the offshore Shimokita Peninsula, Japan was found to be related to Ga0114923_10000127 and Ga0209976_10000148 originating from the sediment samples from the Sumatra, Indian Ocean (Fig. S1), attesting to the consistency of this emerging group of Asgard MGEs.

The seven MGEs encode diverse proteins involved in DNA replication, repair and metabolism, which are common in MGE and viral genomes but, with the exception of 7H_42, Ga0114923_10000127 and Ga0209976_10000148 which form a group, display little overlap in gene content (see below). Nevertheless, 8H_18, 10H_0 and 7H_42 encode Topo mini-A homologs. Phylogenetic analysis of these proteins showed that, whereas 10H_0 and 7H_42 formed a clade with the Topo mini-A of wyrdvirus WyrdV4, 7H_42 branched among other archaeal sequences (Extended Data 4), suggestive of active exchange of Topo mini-A genes among archaeal viruses and MGEs. The 10H_0 and 7H_42-like MGEs as well as verdandiviruses and wyrdviruses encode multiple non-orthologous Zn-finger proteins, which might be involved in transcription regulation or mediate protein-protein interactions. 10H_0 and 7H_42-like MGEs also share homologs of proliferating cellular nuclear antigen (PCNA) and transcription initiation factor B (TFB) (Fig. S1), both of which have been previously identified in archaeal viruses. For instance, PCNA is encoded by several tailed archaeal viruses infecting halophilic archaea 1,2 and spindle-shaped viruses of Nitrososphaeria 3 , whereas TFB homologs are encoded by certain rod-shaped viruses infecting hyperthermophilic Thermoproteota 4 . 10H_0 also encodes Cdc6/Orc1-like origin recognition protein, nucleoside 2-deoxyribosyltransferase, DNA lyase, MazG-like nucleotide pyrophosphohydrolase and bifunctional (p)ppGpp synthase/hydrolase as well as several DNA methyltransferases and nucleases. By contrast, 7H_42-like MGEs encode a DNA primase-superfamily 3 helicase fusion protein that are commonly found in diverse MGEs including diverse varidnaviruses infecting eukaryotes, a Rad51-like recombinase, several nucleases and chromatin-associated proteins containing the HMG domain. The larger elements also encode auxiliary metabolic genes, including PAPS reductase, sulfatase, methylthiotransferase, and enzymes involved in carbohydrate metabolism, which could boost the metabolic activities of the respective hosts. For the smaller contigs, 8H_18 and 8H_67, the vast majority of genes were refractory to functional annotation even using the most sensitive available sequence similarity detection tools, such as HHpred 5 .

Auxiliary gene content of asgardarchaeal viruses

By dsDNA virus standards, genomes of verdandiviruses, skuldviruses and wyrdviruses are relatively small (≤20 kb). Thus, the corresponding gene contents are streamlined to include largely the core functions required for virion morphogenesis and genome replication. Nevertheless, some of these viruses encode auxiliary functions, including metabolic genes. In particular, verdandivirus VerdaV1 (and 10H_0 MGE) encode phosphoadenosine phosphosulfate (PAPS) reductase (also known as CysH), an enzyme reducing 3′-phosphoadenylylsulfate to phosphoadenosine-phosphate using thioredoxin as an electron donor. PAPS reductases have been previously identified in certain bacteriophages [6][7][8] and tailed haloarchaeal viruses 1 , where they are thought to confer selective advantage to the host cells through facilitating sulfur metabolism and/or synthesis of sulfur-containing amino acids 7 . PAPS reductase of VerdaV1 might perform a similar function.

Wyrdviruses WyrdV2 and WyrdV6 carry a block of three genes coding for dUTPase, thymidylate synthase X (ThyX) and an uncharacterized protein that is conserved in some phages and is annotated as nucleotide modification associated domain 1 protein (PF07659.13, DUF1599) (Fig. 5). This putative operon is likely to be involved in the biosynthesis of thymidylate from dUTP, to increase the pool of nucleotides available for the synthesis of viral DNA. WyrdV3 encodes a homolog of the nucleoside pyrophosphohydrolase MazG, which in bacteria prevents programmed cell death by degrading the central alarmone, ppGpp 9 . MazG is highly conserved in tailed bacteriophages infecting cyanobacteria 10 . Biochemical characterization of a cyanophage MazG has shown that, instead of degrading ppGpp, it preferentially hydrolyses dGTP and dCTP 11 . Thus, MazG homolog in WyrdV3 might either function in disarming antiviral systems triggered by nucleotide-based alarmones, such as ppGpp, or in adjusting the intracellular nucleotide concentrations for optimal viral genome synthesis. Notably, MazG homologs are also encoded by asgardarchaeal MGEs 10H_0, 7H_42, Ga0114923_10000127 and Ga0209976_10000148 (Fig. S2).

None of the known archaeal viruses encodes its own RNA polymerase 12 . Nevertheless, various transcription regulators with HTH, Zn-finger or ribbon-helix-helix domains are abundantly encoded in archaeal virus genomes 13 . This is also the case with asgardarchaeal viruses described herein. Verdandiviruses and wyrdviruses encode multiple non-orthologous Zn-finger proteins, whereas skuldviruses encode several proteins with HTH domains (Fig. 4a). In addition, WyrdV1 (as well as 10H_0, 7H_42, Ga0114923_10000127 and Ga0209976_10000148) encodes a transcription initiation factor B (TFB), a homolog of eukaryotic TFIIB, which guides the initiation of RNA transcription 14 . Among archaeal viruses, TFB homologs have been previously identified only in certain rod-shaped viruses infecting hyperthermophilic archaea 4 . Thus, Asgard viruses appear to fully rely on the core transcription machinery of their hosts but encode various transcription factors that could be involved in the recruitment of this machinery for expression of viral genes as well as in the regulation of virus gene transcription. As mentioned above, some of the genes regulated by these transcription factors are likely to encode antidefense proteins.

WyrdV1 and WyrdV3 encode homologs of the carbohydrate-specific 3'-O-methyltransferase 15 . In many archaeal viruses, the structural proteins are glycosylated by either the virus or host encoded glycosyltransferases, although the biological role of this post-translational modification remains unclear. The methyltransferase of WyrdV1 and WyrdV3 could participate in modification of the glycans attached to the virion proteins.

Supplementary references


Cristiana Gomes
email: cristiana.gomes@sophia.inria.fr

Stéphane Pérennes
email: stephane.perennes@sophia.inria.fr

Patricio Reyes
email: patricio.reyes@sophia.inria.fr

Hervé Rivano
email: herve.rivano@sophia.inria.fr

Bandwidth Allocation in Radio Grid Networks

In this paper we give exact or almost exact bounds for the continuous gathering problem on grids. Under very general hypothesis on the traffic demand, we mainly prove that the throughput is determined by the bottleneck around the base station. We deal with two cases: the base station located in the center and in the corner. We use dual lower bounds and describe a protocol which is optimal when the traffic is uniform.

Introduction

The routing problem of steady traffic demands in a radio network has been studied extensively in the literature. In [START_REF] Klasing | On the complexity of bandwidth allocation in radio networks[END_REF] it was proven that if traffic demands are sufficiently steady the problem can be expressed in an independent form of the interference model as the Round Weighting Problem (RWP). We deal with a special case of RWP that considers the gathering of the flow. We represent nodes by the vertices of a transmission graph G = (V, E). The edges of this graph connect nodes that can effectively communicate. The interference model is introduced by providing an implicit definition of the set of possible rounds R . We take a simple model of interference where a round is any set of pairwise disjoint edges at distance at least d s I + 1 (Manhattan distance). It defines a symmetric interference model that permits the calls to happen in both directions (download or upload).

The RWP is then defined as follows: The traffic demands are represented by a flow demand f (u, v) : V ×V → N and one wishes to find a (positive) weight function w : R → R + that enables the flow demands to be carried over the network. The objective MinRW is then to minimize the total weight (namely w(R ) = ∑ R∈R w(R)).

In the case of a general transmission graph with an arbitrary traffic pattern the problem is very difficult to approximate, indeed, to approximate the RWP within n 1-ε is NP-Hard [START_REF] Klasing | On the complexity of bandwidth allocation in radio networks[END_REF]. A practically important case is the Gathering (or personalized broadcasting): the traffic pattern corresponds then to a simple flow, i.e. all demands are directed toward a single node called the BS (Base Station). Gathering is easier to approximate since a simple 4-approximation does exist, but the problem remains NP-Hard. Instances on a grid are tractable mainly due to the local structure of the grid. Note also that the structure of the transmission graph plays a central role, if G is a grid or a unit disk graph the RWP admits a PTAS but remains NP-Hard.

In [START_REF] Bermond | Efficient gathering in radio grids with interference[END_REF], a similar problem, the Round Scheduling Problem (RSP) was treated. The relation with the RWP is the following: if one must repeat rounds scheduling many times then the problem is equivalent to the RWP . The RSP is quite harder to solve than our problem which can be be considered either as a limited case or relaxation. Not surprisingly we obtain not only simpler formulae than Bermond and Peters, but they are valid for a larger class of traffic patterns. Note that, in [START_REF] Bermond | Efficient gathering in radio grids with interference[END_REF] d I > 1 and it is not symmetric because they deal with the exact case of gathering (directed interference). In this paper we study RWP on 2-dimensional grid graphs considering the interference distance d s I = 1 (but our method can be extended to any d s I ). The most basic case is d s I = 0, where R is simply the set of the matchings of G. Since all the traffic demands have as destination/source the BS ( f (u, v) = 0 when v = BS) we simply note f (u, BS) as f (u). We denote S j the set of nodes at distance j of the BS, and E j = (S j , S j-1 ) the set of arcs of the grid connecting the nodes in S j to S j-1 . For example, S 1 represents the set of 4 nodes neighbors of BS and E 1 consists of the 4 edges ending in BS.

Lower bounds

First we recall the dual lower bound from [START_REF] Klasing | On the complexity of bandwidth allocation in radio networks[END_REF]: Given a (positive) length function l(e) on the edges of the transmission graph, we define l(u, BS) or simply l(u) as the minimum length of a path connecting u to BS. Since the problem is homogeneous the dual is indeed:

Maximize ∑ l(u) f (u) with l(R) ≤ 1, ∀R ∈ R . Then MinRW ≥ ∑ l(u) f (u) max R∈R l(R) .

Uniform traffic case

In the uniform case, we consider that all the nodes have the same flow demand. Without loss of generality, we suppose f (u) = 1 for all u ∈ V except BS. We denote T the total traffic demand ∑ v∈V f (u). In this case, T = N -1 where N is the number of nodes of the grid. We define T ′ as the traffic demand that must cross the arcs at distance 2 of BS in order to be gathered. Thus,

T ′ = T -∑ u∈Γ(BS) f (u)
, where Γ(BS) denotes the set of neighbors of BS.

Base Station in the center

Theorem 1 Given a grid with the BS in the center, MinRW = T + T ′ 4 = 5 4 N -9 4 .

Proof: The proof has two parts. The first part consists in finding a feasible solution for the dual problem. This solution is then, a lower bound for our RWP . In the second part, we find an upper bound given by a feasible solution of the original problem. Since there is no gap between both lower and upper bounds, the result follows.

(Lower Bound) The edges with strictly positive values are depicted in figure 1. The edges e ∈ E 1 have l(e) = 1. It comes from the fact that at most one edge in E 1 can be activated for each round.

The edges e ∈ E 2 have l(e) = 1 4 , because it is possible to activate at most 4 edges in a round. For all the remaining edges l(e) = 0. The minimum length of the path connecting u to BS, l(u), is therefore 5 4 except for the 4 neighbors of BS. (Upper Bound) We gather the traffic using the 4 adjacent arcs to the BS. Moreover, all the flow at distance larger than 2 will be collected by the 4 full arcs at distance 2 as shown in figures 1 and 2. We denote e 1 i (1 ≤ i ≤ 4) the 4 arcs adjacent to the BS and e 2 i the 4 arcs at distance 2.

We define R i (R 1 , R 2 , R 3 and R 4 ) as the subset of rounds using the arc e 1 i and R 5 as the subset of rounds using e 2 i . Then, in order to attain the bound, we need to use only rounds in these subsets. and E j+2 . So, we have 13 types of rounds called R 5 ∈ R 5 and R i j ∈ R i , 1 ≤ i ≤ 4, 0 ≤ j ≤ 2. R i j will contain arcs either e 1 i or arcs in E j+3p (p ≥ 1). R 5 contains only the arcs e2 i . Note that, except E 2 , each E j use only rounds type R i, j mod 3 . We will choose the weights such that w(R i j ) = T 12 and w(R 5 ) = T ′ 4 . Doing so we attain the lower bound but we have a problem with the 4 non-filled nodes in S 2 (in figure 3) which cannot be directly routed to BS via the edges in e 2 i . If we use an edge of E 2 but different from e 2 i , we can activate at the same round at most 3 edges of E 2 instead 4 (from e 2 i ) and we will not reach the lower bound.

To deal with this difficulty, we split each round of type R i0 in two new rounds: The special round R i0 s used to move the flow of one problematic node from S 2 to S 3 and the normal round R i0 n where all the arcs are directed to the BS. The weights proposed for these rounds are w(R i0 s ) = 1, and

w(R i0 n ) = T 12 -1.
Note that, for arcs in E j with j ≥ 3, calls used by both types of rounds R i0 s and R i0 n are exactly the same. The differences between these types of rounds in arcs in E 1 , E 2 and E 3 are presented in figures 2 and 3. Finally, we have used the rounds

R i0 s , R i0 n , R i1 , R i2 , R 5 , 1 ≤ i ≤ 4.
Their respective weights are w(R i0 s ) = 1, w(R i0 n ) = T 12 -1, w(R i j ) = T 12 , and w(R 5 ) = T ′ 4 . Now, we need to show that there is a routing of the flow that respects the capacity induced of the arcs by our round weights. Note first that, globally, the capacity by each E i , i ≥ 2 is at least T ′ . This capacity is enough to transmit the flow desired between E i+1 to E i and so on. Now, we propose a routing such that all the nodes in S i receive the same quantity of flow from S i+1 . A special case occurs when distributing the flow between the nodes in S 3 . As well as considering the flow from S 4 we need to consider the flow from the 4 special nodes in S 2 . Note that by the symmetry of the grid, we can only take into account the routing of one quadrant of the grid, and then we repeat and rotate the configuration to the rest of the quadrants.

Base Station in the corner

Theorem 2 Given a grid with the BS in the corner,

MinRW = T + T ′ 2 + 1 2 = 3 2 N -2.
Proof: The structure of the proof is similar to Theorem 1.

(Lower Bound) The values of the lengths l(e) are depicted in figure 4. The minimum length of the path connecting u to BS, l(u), is therefore 3 2 except for X and Y which is l(u) = 1, and for the node z which is l(u) = 2. Then MinRW ≥ T + T ′ 2 + 1 2 , where the term 1 2 can be explained by the extra cost needed to send traffic from node z (the problematic node) to the usual route.

(Upper Bound) According to the dual values shown in figure 4, any scheme that costs about 3T sets of rounds R i , each set must be split as shown in figure 5 to completely cover the grid. Let T " = T ′f (z) = T ′ -1, we propose the respective weights: w(R 1 ) = T 2 , w(R 2 ) = T 2 , w(R 3A ) = T " 2 and w(R 3B ) = 1. The set R 3 will be used to cover the arcs E i when (i + 1) mod 3 = 0, we use R 1 and R 2 otherwise. It follows that we can cover the arcs E i at least T " times. Thus, we used a total weight of T + T " 2 + 1 that matches the lower bound. A possible routing respecting our round weights (induced capacity) is such that all the nodes in S i receive the same quantity of flow from S i+1 .

Generalizations

The proof given for an arbitrary traffic can be generalized to most traffics as follows. From lemma 1, we remark that outside the radius 3 ball the round R 5 is never used. So, a weight of T /4 is unused in most of the network and can be used to balance the traffic a priori. Thus, balancing the traffic turns into a transportation problem in the grid. We can prove that a non uniform demand can be re-routed to a uniform one if no node contains more than βT units of traffic, and the 5T /4 bound holds. The same idea can also be applied to the case of an arbitrary BS location. The flow must then be routed toward the radius 3 ball in a uniform way and this is possible as soon as the BS is far enough (distance ≥ d a ) from the borders. The quality of the constants β, d a depend on how precise are the algorithms.

Another demonstration for the same results consists in finding k long non-interfering paths (with k the degree of BS) for each node through the BS. The gathering protocol is then quite simple since it sends the traffic of each node using the k paths in a balanced way. This should prove that the gathering time is T (1 + 1 k ) + o(T ) for most practical networks.

Fig. 2 :Fig. 3 :

 23 Fig. 1: Dual values

  Fig. 4: Dual values

† C. Gomes is funded by CAPES, Brazil. P. Reyes is funded by CONICYT/INRIA, Chile/France. This work has been partially funded by European project ist/fet aeolus, anr-jc osera, and arc carma.

units of traffic through each of the nodes X and Y . We only need three