Resistance to three pathogens in the endangered winter-run chinook salmon (<i>Oncorhynchus tshawytscha</i>): effects of inbreeding and major histocompatibility complex genotypes
Bibliographic record
Abstract
We have carried out the first major infectivity trial to examine differential genetic resistance in fish for pathogens. We used captive-bred, endangered winter-run chinook salmon (Oncorhynchus tshawytscha) to determine resistance to three pathogens: the bacterium, Listonella (Vibrio) anguillarum, infectious hematopoietic necrosis virus (IHNV), and Myxobolus cerebralis, the parasite that causes whirling disease. We compared resistance to these three pathogens between inbred and outbred salmon and between siblings that were heterozygous or homozygous for a class II gene in the major histocompatibility complex (MHC). In two of five different comparisons, we found significant genetic effects on disease resistance. First, MHC heterozygotes had a higher survival than MHC homozygotes when exposed to IHNV and the selection disadvantage of homozygotes was estimated to be 8.5%. Second, outbred fish had a higher resistance (or lower infection severity) than inbred fish when exposed to M. cerebralis. Using a quantitative genetics approach, it appears that there are slightly more than three gene equivalents segregating that would result in no resistance to M. cerebralis when homozygous. Overall, our investigation suggests that pathogen susceptibility in the winter-run chinook salmon will increase if further genetic variation is lost in this endangered species.
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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 | 0.000 |
| 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) | 0.001 | 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".