Previously unknown and highly divergent ssDNA viruses populate the oceans
Bibliographic record
Abstract
Single-stranded DNA (ssDNA) viruses are economically important pathogens of plants and animals, and are widespread in oceans; yet, the diversity and evolutionary relationships among marine ssDNA viruses remain largely unknown. Here we present the results from a metagenomic study of composite samples from temperate (Saanich Inlet, 11 samples; Strait of Georgia, 85 samples) and subtropical (46 samples, Gulf of Mexico) seawater. Most sequences (84%) had no evident similarity to sequenced viruses. In total, 608 putative complete genomes of ssDNA viruses were assembled, almost doubling the number of ssDNA viral genomes in databases. These comprised 129 genetically distinct groups, each represented by at least one complete genome that had no recognizable similarity to each other or to other virus sequences. Given that the seven recognized families of ssDNA viruses have considerable sequence homology within them, this suggests that many of these genetic groups may represent new viral families. Moreover, nearly 70% of the sequences were similar to one of these genomes, indicating that most of the sequences could be assigned to a genetically distinct group. Most sequences fell within 11 well-defined gene groups, each sharing a common gene. Some of these encoded putative replication and coat proteins that had similarity to sequences from viruses infecting eukaryotes, suggesting that these were likely from viruses infecting eukaryotic phytoplankton and zooplankton.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".