Microbes drive most ecosystems and are modulated by viruses that impact their lifespan, gene flow and metabolic outputs. However, ecosystem-level impacts of viral community diversity remains difficult to assess due to classification issues and few reference genomes. Here we establish a ~12-fold expanded global ocean DNA virome dataset of 195,728 60 viral populations, now including the Arctic Ocean, and validate that these populations form discrete genotypic clusters. Meta-community analyses revealed five ecological zones throughout the global ocean, including two distinct Arctic regions. Across the zones, local and global patterns and drivers in viral community diversity were established for both macrodiversity (interpopulation diversity) and microdiversity (intra-population genetic variation). These patterns 65 sometimes, but not always, paralleled those from macro-organisms and revealed temperate and tropical surface waters and the Arctic as biodiversity hotspots and mechanistic hypotheses to explain them. Such further understanding of ocean viruses is critical for broader inclusion in ecosystem models. Introduction: 70Biodiversity is essential for maintaining ecosystem functions and services (reviewed by Tilman et al., 2014). In the oceans, the vast majority of biodiversity is contained within the microbial fraction containing prokaryotes and eukaryotic microbes, which represents ~60% of its biomass (Bar-On et al., 2018). Meta-analyses looking at changes in marine biodiversity show that biodiversity loss increasingly impairs the ocean's capacity to produce food, maintain water 75 quality, and recover from perturbations (Worm et al., 2006). To date, marine conservation efforts have focused on specific organismal communities, such as fisheries or coral reefs, rather than conserving whole ecosystem biodiversity. However, emerging studies across diverse sampled, global-scale, viruses-to-fish-larvae datasets (de Vargas et al., 2015; Sunagawa et al., 125 2015;Brum et al., 2015;Lima-Mendez et al., 2015;Pesant et al. 2015;Roux et al., 2016), and help establish foundational ecological hypotheses for the field and a roadmap for the broader life sciences community to better study viruses in complex communities. Results & Discussion:The dataset. The Global Ocean Viromes 2.0 (GOV 2.0) dataset is derived from 3.95 Tb 130 of sequencing across 145 samples distributed throughout the world's oceans ( Fig. 1A and Table S3; see Methods). These data build on the prior GOV dataset (Roux et al., 2016) by increased sequencing for mesopelagic samples (defined in our dataset as waters between 150m to 1,000m) and upgrading assemblies, both of which drastically improved sampling of the ocean viruses in these samples (results below). Additionally, we added 41 new samples derived from the Tara 135Oceans Polar Circle (TOPC) expedition, which traveled 25,000 km around the Arctic Ocean in 2013. These 41 Arctic Ocean viromes were generated to represent the most significantly climateimpacted region of the ocean, and an extreme environment. N...

Background Viruses are a significant player in many biosphere and human ecosystems, but most signals remain “hidden” in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools. Results Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2’s modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity. Conclusion With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available (https://bitbucket.org/MAVERICLab/virsorter2), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse (https://de.cyverse.org/de).

Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are insufficiently studied outside disease settings. In this study, we analyzed ≈28 terabases of Global Ocean RNA sequences to expand Earth’s RNA virus catalogs and their taxonomy, investigate their evolutionary origins, and assess their marine biogeography from pole to pole. Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding. “Species”-rank abundance determination revealed that viruses of the new phyla “ Taraviricota ,” a missing link in early RNA virus evolution, and “ Arctiviricota ” are widespread and dominant in the oceans. These efforts provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.

Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as ‘hypothetical protein’ or the equivalent. Cenote-Taker 2, a virus discovery and annotation tool available on command line and with a graphical user interface with free high-performance computation access, utilizes highly sensitive models of hallmark virus genes to discover familiar or divergent viral sequences from user-input contigs. Additionally, Cenote-Taker 2 uses a flexible set of modules to automatically annotate the sequence features of contigs, providing more gene information than comparable tools. The outputs include readable and interactive genome maps, virome summary tables, and files that can be directly submitted to GenBank. We expect Cenote-Taker 2 to facilitate virus discovery, annotation, and expansion of the known virome.

DNA viruses are increasingly recognized as influencing marine microbes and microbe-mediated biogeochemical cycling. However, little is known about global marine RNA virus diversity, ecology, and ecosystem roles. In this study, we uncover patterns and predictors of marine RNA virus community- and “species”-level diversity and contextualize their ecological impacts from pole to pole. Our analyses revealed four ecological zones, latitudinal and depth diversity patterns, and environmental correlates for RNA viruses. Our findings only partially parallel those of cosampled plankton and show unexpectedly high polar ecological interactions. The influence of RNA viruses on ecosystems appears to be large, as predicted hosts are ecologically important. Moreover, the occurrence of auxiliary metabolic genes indicates that RNA viruses cause reprogramming of diverse host metabolisms, including photosynthesis and carbon cycling, and that RNA virus abundances predict ocean carbon export.

Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as “hypothetical protein” or the equivalent. Cenote-Taker2, a virus discovery and annotation tool available on command line and with a graphical user interface with free high-performance computation access, utilizes highly sensitive models of hallmark virus genes to discover familiar or divergent viral sequences from user-input contigs. Additionally, Cenote-Taker2 uses a flexible set of modules to automatically annotate the sequence features of contigs, providing more gene information than comparable tools. The outputs include readable and interactive genome maps, virome summary tables, and files that can be directly submitted to GenBank. We expect Cenote-Taker2 to facilitate virus discovery, annotation, and expansion of the known virome.

Microbes drive most ecosystems and are modulated by viruses that impact their lifespan, gene flow and metabolic outputs. However, ecosystem-level impacts of viral community diversity remains difficult to assess due to classification issues and few reference genomes. Here we establish a ~12-fold expanded global ocean DNA virome dataset of 195,728 60 viral populations, now including the Arctic Ocean, and validate that these populations form discrete genotypic clusters. Meta-community analyses revealed five ecological zones throughout the global ocean, including two distinct Arctic regions. Across the zones, local and global patterns and drivers in viral community diversity were established for both macrodiversity (interpopulation diversity) and microdiversity (intra-population genetic variation). These patterns sometimes, but not always, paralleled those from macro-organisms and revealed temperate and tropical surface waters and the Arctic as biodiversity hotspots and mechanistic hypotheses to explain them. Such further understanding of ocean viruses is critical for broader inclusion in ecosystem models. Results & Discussion: The dataset. The Global Ocean Viromes 2.0 (GOV 2.0) dataset is derived from 3.95 Tb of sequencing across 145 samples distributed throughout the world's oceans (Fig. 1A and Table S3; see Methods). These data build on the prior GOV dataset (Roux et al., 2016) by increased sequencing for mesopelagic samples (defined in our dataset as waters between 150m to 1,000m) and upgrading assemblies, both of which drastically improved sampling of the ocean viruses in these samples (results below). Additionally, we added 41 new samples derived from the Tara Oceans Polar Circle (TOPC) expedition, which traveled 25,000 km around the Arctic Ocean in 2013. These 41 Arctic Ocean viromes were generated to represent the most significantly climateimpacted region of the ocean, and an extreme environment. No such metagenome-based viral data exist for the Arctic region (Deming & Collins 2017), and more generally, for many planktonic organisms, systematic sampling is uneven throughout the Arctic Ocean (CAFF State of the Arctic Marine Biodiversity Report) due to geopolitical and physical challenges of sampling these regions. The first step to studying viral biodiversity from the assembled GOV 2.0 dataset (see Methods and Fig. S1A) was to identify contigs that likely derive from viruses using tools that collectively utilize homology to viral reference databases, probabilistic models on viral genomic features, and viral k-mer signatures (see Methods). These putative viral contigs were then assigned to 'populations', which are currently defined as viral contigs ≥10 kb where ≥70% of the shared genes have ≥95% average nucleotide identity (ANI) across its members (Brum et al., 2015; Roux et al., 2016; Roux et al., 2018; population definition also discussed below). This process identified 195,728 viral populations in the GOV 2.0 dataset, which is a ~12-fold increase over the 15,280 identified in the original GOV dataset and ass...

Geminiviruses (family Geminiviridae) possess single-stranded circular DNA genomes that are replicated by cellular polymerases in plant host cell nuclei. In their hosts, geminivirus populations behave as ensembles of mutant and recombinant genomes, known as viral quasispecies. This favors the emergence of new geminiviruses with altered host range, facilitating new or more severe diseases or overcoming resistance traits. In warm and temperate areas several whitefly-transmitted geminiviruses of the genus Begomovirus cause the tomato yellow leaf curl disease (TYLCD) with significant economic consequences. TYLCD is frequently controlled in commercial tomatoes by using the dominant Ty-1 resistance gene. Over a 45 day period we have studied the diversification of three begomoviruses causing TYLCD: tomato yellow leaf curl virus (TYLCV), tomato yellow leaf curl Sardinia virus (TYLCSV) and tomato yellow leaf curl Malaga virus (TYLCMaV, a natural recombinant between TYLCV and TYLCSV). Viral quasispecies resulting from inoculation of geminivirus infectious clones were examined in plants of susceptible tomato (ty-1/ty-1), heterozygous resistant tomato (Ty-1/ty-1), common bean, and the wild reservoir Solanum nigrum. Differences in virus fitness across hosts were observed while viral consensus sequences remained invariant. However, the complexity and heterogeneity of the quasispecies were high, especially in common bean and the wild host. Interestingly, the presence or absence of the Ty-1 allele in tomato did not lead to differences in begomovirus mutant spectra. However, the fitness decrease of TYLCSV and TYLCV in tomato at 45 dpi might be related to an increase in CP (Coat protein) mutation frequency. In Solanum nigrum the recombinant TYLCMaV, which showed lower fitness than TYLCSV, at 45 dpi actively explored Rep (Replication associated protein) ORF but not the overlapping C4. Our results underline the importance of begomovirus mutant spectra during infections. This is especially relevant in the wild reservoir of the viruses, which has the potential to maintain highly diverse mutant spectra without modifying their consensus sequences.