ORIGINAL ARTICLE MHC genetic structure and divergence across populations of Chinook salmon
Bibliographic record
Abstract
The major histocompatibility complex (MHC) is thought to be under strong selection pressure because of its integral role in pathogen recognition. Consequently, patterns of MHC genetic variation should reflect selection pressures across the landscape. We examined genetic variation and popula-tion genetic structure at the MHC class I-A1 and class II-B1 exons in five Chinook salmon (Oncorhynchus tshawytscha) populations from two geographic regions in British Columbia, Canada. We then compared estimates of population struc-ture at the MHC genes with neutral estimates based on microsatellites to examine the potential for local adapta-tion at the MHC. Chinook salmon are in decline throughout much of their native range and understanding the degree of local adaptation exhibited by the MHC may be important in conservation planning. Comparisons among populations yielded higher G0ST estimates for the MHC class I than expected under neutrality based on the microsatellites. In contrast, the MHC class II tended to exhibit lower G0ST values than did the microsatellites. These results suggest that across populations unique selection pressures are driving allele frequency differences at the MHC class I but that the MHC class II may be the subject of homogenizing selection. Rates of nonsynonymous versus synonymous substitutions found in codons associated within the MHC class I and II peptide-binding regions provided strong evidence of positive selection. Together, these results support the hypothesis that selection is influencing genetic variation at the MHC, but suggest that selection pressures may vary at the two classes of loci both at the sequence and population levels.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".