(Lack of) Genetic Diversity in Immune Genes Predates Glacial Isolation in the North American Mountain Goat (Oreamnos americanus)
Bibliographic record
Abstract
The major histocompatibility complex (MHC) plays an important role in an organism's ability to respond to pathogens. Immunogenetic diversity is advantageous as it permits the recognition of more external antigens. For this reason, MHC and immune gene variation are considered a barometer for the genetic health of wild populations. Mountain goats (Oreamnos americanus) were previously shown to have little variation at the MHC Class II Oram-DRB locus, which was attributed to population bottlenecks during the last glacial maximum (LGM). In this paper, we extended the analysis of immunogenetic variability in mountain goats to 5 genes representing the 3 classes of MHC gene (Class I OLA, Class II DRA and DRB, and Class III TNF-α) and the natural resistance-associated macrophage protein. We sequenced approximately 3000 bp from 31 individuals sampled across the range of mountain goats and found very low levels of diversity (1-3 polymorphic sites per gene) with the exception of the Class I Oram-OLA gene. Oram-OLA was nearly 30 times more diverse than the other immune genes and appears to represent a source of increased immunogenetic diversity. This diversity may be attributed to multiple loci, mediated by pathogen exposure, or potentially influenced by social factors. The distribution of SNPs was not associated with refugial history, suggesting that the current distribution of immunogenetic diversity was present prior to the LGM. These data suggest that although they have low levels of diversity at the 4 of 5 immune loci, mountain goats may be better equipped for future climate oscillations and pathogen exposure than previously thought.
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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 | 0.001 |
| 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".