Red and white Chinook salmon: genetic divergence and mate choice
Bibliographic record
Abstract
Chinook salmon (Oncorhynchus tshawytscha) exhibit extreme differences in coloration of skin, eggs and flesh due to genetic polymorphisms affecting carotenoid deposition, where colour can range from white to bright red. A sympatric population of red and white Chinook salmon occurs in the Quesnel River, British Columbia, where frequencies of each phenotype are relatively equal. In our study, we examined evolutionary mechanisms responsible for the maintenance of the morphs, where we first tested whether morphs were reproductively isolated using microsatellite genotyping, and second, using breeding trials in seminatural spawning channels, we tested whether colour assortative mate choice could be operating to maintain the polymorphism in nature. Next, given extreme difference in carotenoid assimilation and the importance of carotenoids to immune function, we examined mate choice and selection between colour morphs at immune genes (major histocompatibility complex genes: MHC I-A1 and MHC II-B1). In our study, red and white individuals were found to interbreed, and under seminatural conditions, some degree of colour assortative mate choice (71% of matings) was observed. We found significant genetic differences at both MHC genes between morphs, but no evidence of MHC II-B1-based mate choice. White individuals were more heterozygous at MHC II-B1 compared with red individuals, and morphs showed significant allele frequency differences at MHC I-A1. Although colour assortative mate choice is likely not a primary mechanism maintaining the polymorphisms in the population, our results suggest that selection is operating differentially at immune genes in red and white Chinook salmon, possibly due to differences in carotenoid utilization.
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 | 0.001 |
| 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) | 0.001 | 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".