CLINAL VARIATION IN MHC DIVERSITY WITH TEMPERATURE: EVIDENCE FOR THE ROLE OF HOST?PATHOGEN INTERACTION ON LOCAL ADAPTATION IN ATLANTIC SALMON
Bibliographic record
Abstract
In vertebrates, variability at genes of the Major Histocompatibility Complex (MHC) represents an important adaptation for pathogen resistance, whereby high allelic diversity confers resistance to a greater number of pathogens. Pathogens can maintain diversifying selection pressure on their host's immune system that can vary in intensity based on pathogen richness, pathogen virulence, and length of the cohabitation period, which tend to increase with temperature. In this study, we tested the hypothesis that genetic diversity of MHC increases with temperature along a latitudinal gradient in response to pathogen selective pressure in the wild. A total of 1549 Atlantic salmon from 34 rivers were sampled between 46 degrees N and 58 degrees N in Eastern Canada. The results supported our working hypothesis. In contrast to the overall pattern observed at microsatellites, MHC class II allelic diversity increased with temperature, thus creating a latitudinal gradient. The observed temperature gradient was more pronounced for MHC amino acids of the peptide-binding region (PBR), a region that specifically binds to pathogens, than for the non-PBR. For the subset of rivers analyzed for bacterial diversity, MHC amino acid diversity of the PBR also increased significantly with bacterial diversity in each river. A comparison of the relative influence of temperature and bacterial diversity revealed that the latter could have a predominant role on MHC PBR variability. However, temperature was also identified as an important selective agent maintaining MHC diversity in the wild. Based on the bacteria results and given the putative role of temperature in shaping large-scale patterns of pathogen diversity and virulence, bacterial diversity is a plausible selection mechanism explaining the observed association between temperature and MHC variability. Therefore, we propose that genetic diversity at MHC class II represents local adaptation to cope with pathogen diversity in rivers associated with different thermal regimes. This study illuminates the link between selection pressure from the environment, host immune adaptation, and the large-scale genetic population structure for a nonmodel vertebrate in the wild.
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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 | 0.000 | 0.001 |
| 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".