The complete genomes of three viruses assembled from shotgun libraries of marine RNA virus communities
Bibliographic record
Abstract
BACKGROUND: RNA viruses have been isolated that infect marine organisms ranging from bacteria to whales, but little is known about the composition and population structure of the in situ marine RNA virus community. In a recent study, the majority of three genomes of previously unknown positive-sense single-stranded (ss) RNA viruses were assembled from reverse-transcribed whole-genome shotgun libraries. The present contribution comparatively analyzes these genomes with respect to representative viruses from established viral taxa. RESULTS: Two of the genomes (JP-A and JP-B), appear to be polycistronic viruses in the proposed order Picornavirales that fall into a well-supported clade of marine picorna-like viruses, the characterized members of which all infect marine protists. A temporal and geographic survey indicates that the JP genomes are persistent and widespread in British Columbia waters. The third genome, SOG, encodes a putative RNA-dependent RNA polymerase (RdRp) that is related to the RdRp of viruses in the family Tombusviridae, but the remaining SOG sequence has no significant similarity to any sequences in the NCBI database. CONCLUSION: The complete genomes of these viruses permitted analyses that resulted in a more comprehensive comparison of these pathogens with established taxa. For example, in concordance with phylogenies based on the RdRp, our results support a close homology between JP-A and JP-B and RsRNAV. In contrast, although classification of the SOG genome based on the RdRp places SOG within the Tombusviridae, SOG lacks a capsid and movement protein conserved within this family and SOG is thus likely more distantly related to the Tombusivridae than the RdRp phylogeney indicates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".