Plumage microbiota covaries with the major histocompatibility complex in blue petrels
Bibliographic record
Abstract
To increase fitness, a wide range of vertebrates preferentially mate with partners that are dissimilar at the major histocompatibility complex (MHC) or that have high MHC diversity. Although MHC often can be assessed through olfactory cues, the mechanism by which MHC genes influence odour remains largely unclear. MHC class IIB molecules, which enable recognition and elimination of extracellular bacteria, have been suggested to influence odour indirectly by shaping odour-producing microbiota, i.e. bacterial communities. However, there is little evidence of the predicted covariation between an animal's MHC genotype and its bacterial communities in scent-producing body surfaces. Here, using high-throughput sequencing, we tested the covariation between MHC class IIB genotypes and feather microbiota in the blue petrel (Halobaena caerulea), a seabird with highly developed olfaction that has been suggested to rely on oduor cues during an MHC-based mate choice. First, we show that individuals with similar MHC class IIB profiles also have similar bacterial assemblages in their feathers. Then, we show that individuals with high MHC diversity have less diverse feather microbiota and also a reduced abundance of a bacterium of the genus Arsenophonus, a genus in which some species are symbionts of avian ectoparasites. Our results, showing that feather microbiota covary with MHC, are consistent with the hypothesis that individual MHC genotype may shape the semiochemical-producing microbiota in birds.
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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 | 0.000 |
| 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) | 0.002 | 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".