A remarkably diverse and well-organized virus community in a filter-feeding oyster.

BACKGROUND: Viruses play critical roles in the marine environment because of their interactions with an extremely broad range of potential hosts. Many studies of viruses in seawater have been published, but viruses that inhabit marine animals have been largely neglected. Oysters are keystone species in coastal ecosystems, yet as filter-feeding bivalves with very large roosting numbers and species co-habitation, it is not clear what role they play in marine virus transmission and coastal microbiome regulation. RESULTS: Here, we report a Dataset of Oyster Virome (DOV) that contains 728,784 nonredundant viral operational taxonomic unit contigs (≥ 800 bp) and 3473 high-quality viral genomes, enabling the first comprehensive overview of both DNA and RNA viral communities in the oyster Crassostrea hongkongensis. We discovered tremendous diversity among novel viruses that inhabit this oyster using multiple approaches, including reads recruitment, viral operational taxonomic units, and high-quality virus genomes. Our results show that these viruses are very different from viruses in the oceans or other habitats. In particular, the high diversity of novel circoviruses that we found in the oysters indicates that oysters may be potential hotspots for circoviruses. Notably, the viruses that were enriched in oysters are not random but are well-organized communities that can respond to changes in the health state of the host and the external environment at both compositional and functional levels. CONCLUSIONS: In this study, we generated a first "knowledge landscape" of the oyster virome, which has increased the number of known oyster-related viruses by tens of thousands. Our results suggest that oysters provide a unique habitat that is different from that of seawater, and highlight the importance of filter-feeding bivalves for marine virus exploration as well as their essential but still invisible roles in regulating marine ecosystems. Video Abstract.

Virus classification for viral genomic fragments using PhaGCN2.

Viruses are the most ubiquitous and diverse entities in the biome. Due to the rapid growth of newly identified viruses, there is an urgent need for accurate and comprehensive virus classification, particularly for novel viruses. Here, we present PhaGCN2, which can rapidly classify the taxonomy of viral sequences at the family level and supports the visualization of the associations of all families. We evaluate the performance of PhaGCN2 and compare it with the state-of-the-art virus classification tools, such as vConTACT2, CAT and VPF-Class, using the widely accepted metrics. The results show that PhaGCN2 largely improves the precision and recall of virus classification, increases the number of classifiable virus sequences in the Global Ocean Virome dataset (v2.0) by four times and classifies more than 90% of the Gut Phage Database. PhaGCN2 makes it possible to conduct high-throughput and automatic expansion of the database of the International Committee on Taxonomy of Viruses. The source code is freely available at https://github.com/KennthShang/PhaGCN2.0.

A discussion of RNA virus taxonomy based on the 2020 International Committee on Taxonomy of Viruses report.

RNA viruses have a higher mutation rate than DNA viruses; however, RNA viruses are insufficiently studied outside disease settings. The International Committee on Taxonomy of Viruses (ICTV) is an organization set up by virologists to standardize virus classification. To better understand ICTV taxonomy and the characteristics and rules of different RNA virus families, we analyzed the 3,529 RNA viruses included in the 2020 ICTV report using five widely used metrics: length, host, GC content, number of predicted ORFs, and sequence similarity. The results show that host type has a significant influence on viral genome length and GC content. The genome lengths of virus members within the same genus are quite similar: 98.28% of the genome length differences within any particular genus are less than 20%. The species within those genera containing segmented viruses also have a similar length and number of segments. The number of predicted ORFs in the RNA viral genomes also shows a strong, statistically significant correlation with genome length. We suggest that due to the high mutation rate of RNA virus genomes, current RNA virus classification should mainly rely on protein similarities rather than nucleic acid similarities.