Host genetic variation explains reduced protection of commercial vaccines against Piscirickettsia salmonis in Atlantic salmon
Bibliographic record
Abstract
Vaccination is a widely used control strategy to prevent Piscirickettsia salmonis causing disease in salmon farming. However, it is not known why all the currently available commercial vaccines generally fail to protect against this pathogenic bacteria. Here, we report, from two different populations, that between-family variation is a strong intrinsic factor that determines vaccine protection for this disease. While in some full-sib families, the protection added by vaccination increased the survival time in 13 days in comparison with their unvaccinated siblings; in other families, there was no added protection by vaccination or even it was slightly negative. Resistance to P. salmonis, measured as days to death, was higher in vaccinated than unvaccinated fish, but only a moderate positive genetic correlation was obtained between these traits. This disputes a previous hypothesis, that stated that both traits were fully controlled by the same genes, and challenges the use of unvaccinated fish as gold standard for evaluating and selecting fish resistant to P. salmonis, particularly if the offspring will be vaccinated. More studies are necessary to evaluate if variation in the host immune response to vaccination could explain the between-family differences in resistance observed in vaccinated fish.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".