Variation in <scp>MHC</scp> class <scp>II B</scp> genes in marbled murrelets: implications for delineating conservation units
Bibliographic record
Abstract
Abstract Conserving genetic variation is critical for maintaining the evolutionary potential and viability of a species. Genetic studies seeking to delineate conservation units, however, typically focus on characterizing neutral genetic variation and may not identify populations harboring local adaptations. Here, variation at two major histocompatibility complex (MHC) class II B genes was characterized in four populations of marbled murrelets Brachyramphus marmoratus, a threatened species in which little neutral genetic population structure has been detected. High diversity, as well as evidence of balancing selection, was detected in exon 2 of these genes. Genetic population structure based on MHC markers was uncorrelated to genetic structure estimated with neutral markers, suggesting that selection played a more important role in shaping population structure at these markers than genetic drift. A high proportion of alleles and inferred peptides were unique to a single population, with the Aleutian Islands and southeast Alaska having the highest richness of both. Murrelets sampled in Oregon had low MHC exon 2 allele and inferred peptide richness, and were significantly differentiated from individuals sampled in the Aleutian Islands based on the frequency of exon 2 alleles. In addition, murrelets sampled in Oregon were differentiated from murrelets in both the Aleutian Islands and southeast Alaska based on inferred peptide frequencies, suggesting that the Oregon population could be prioritized for conservation measures. More broadly, combining information from neutral and adaptive genetic markers can improve the delineation of conservation units in threatened species.
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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 | 0.001 | 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) | 0.001 | 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".