Totivirus–satellite coinfection prevalence and host genotype associations in wild <i>Saccharomyces cerevisiae</i>
Bibliographic record
Abstract
Saccharomyces cerevisiae is occasionally infected by dsRNA totiviruses and their toxin-encoding dsRNA satellite nucleic acids. The autonomous totivirus and its satellite can coexist but with an asymmetric dependence of the satellite on the totivirus for replication and maintenance inside the host cell. Satellites provide their yeast hosts with inhibitory toxins and the necessary self-immunity; loss of the satellite equates to loss of toxin immunity. Because these viral elements lack known extracellular stages, and sex is suspected to be rare, they are assumed to be transmitted vertically, implying that infection states should correlate with host genotypes. However, totivirus-satellite coinfections are rarely examined in natural populations, leaving their associations with host genotypes poorly understood. We screened a multiyear, vineyard-associated population of S. cerevisiae isolates from New Zealand to examine the stability of host-virus associations over time, both within and across genotypes. Over half of the wild isolates harbored infections (55%), but less than half of these (37% of infected) had toxin-encoding satellites. Genotypes that persisted across years typically maintained consistent infection states. However, we also observed stepwise transitions from coinfection through infection to an infection-free state, as well as acquisition of totiviruses and satellites. Genotypes clustered strongly by infection state, and population heterozygosity was significantly lower than expected, supporting vertical transmission while suggesting that outcrossing is not responsible for the acquisition of higher infection states. Despite occasional intragenotypic transitions, genotype clustering by infection state remained intact, suggesting that such transitions are transient and that host genotypes may have optimal infection states with regard to totiviruses and their satellites.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".