Comparative analysis of population structure across environments and geographical scales at major histocompatibility complex and microsatellite loci in Atlantic salmon (<i>Salmo salar</i>)
Bibliographic record
Abstract
Evidence of selection acting on major histocompatibility complex (MHC) genes has been illustrated with the analysis of their nucleotide sequences and allele frequency distribution. Comparing the patterns of population differentiation at neutral markers and MHC genes in the wild may provide further insights about the relative role of selection and neutrality in shaping their diversity. In this study, we combine both methods to assess the role of selection on a MHC gene in Atlantic salmon. We compare variation at a MHC class II B locus and microsatellites among 14 samples from seven different rivers and seven subpopulations within a single river system covering a variety of habitats and different geographical scales. We show that diversifying selection is acting on the sites involved in antigen presentation and that balancing selection maintains a high level of polymorphism within populations. Despite important differences in habitat type, the comparison of the population structure at MHC and microsatellites on large geographical scales reveals a correlation between patterns of differentiation, indicating that drift and migration have been more important than selection in shaping population differentiation at the MHC locus. In contrast, strong discrepancies between patterns of population differentiation at the two types of markers provides support for the role of selection in shaping population structure within rivers. Together, these results confirm that natural selection is influencing MHC gene diversity in wild Atlantic salmon although neutral forces may also be important in their evolution.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".