Genetic variation at MHC class II loci influences both olfactory signals and scent discrimination in ring-tailed lemurs
Bibliographic record
Abstract
BACKGROUND: Diversity at the Major Histocompatibility Complex (MHC) is critical to health and fitness, such that MHC genotype may predict an individual's quality or compatibility as a competitor, ally, or mate. Moreover, because MHC products can influence the components of bodily secretions, an individual's body odors may signal its MHC composition and influence partner identification or mate choice. Here, we investigated MHC-based signaling and recipient sensitivity by testing for odor-gene covariance and behavioral discrimination of MHC diversity and pairwise dissimilarity in a strepsirrhine primate, the ring-tailed lemur (Lemur catta). METHODS: First, we coupled genotyping of the MHC class II gene, DRB, with gas chromatography-mass spectrometry of genital gland secretions to investigate if functional genetic diversity is signaled by the chemical diversity of lemur scent secretions. We also assessed if the chemical similarity between individuals correlated with their MHC-DRB similarity. Next, we assessed if lemurs discriminated this chemically encoded, genetic information in opposite-sex conspecifics. RESULTS: We found that both sexes signaled overall MHC-DRB diversity and pairwise MHC-DRB similarity via genital secretions, but in a sex- and season-dependent manner. Additionally, the sexes discriminated absolute and relative MHC-DRB diversity in the genital odors of opposite-sex conspecifics, suggesting that lemur genital odors function to advertise genetic quality. CONCLUSIONS: In summary, genital odors of ring-tailed lemurs provide honest information about an individual's absolute and relative MHC quality. Complementing evidence in humans and Old World monkeys, we suggest that reliance on scent signals to communicate MHC quality may be important across the primate lineage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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 teacher head, 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".