A sexually-selected male weapon characterised by strong additive genetic variance and no evidence for sexually antagonistic polyphenic maintenance
Bibliographic record
Abstract
Sexual selection and sexual antagonism are important drivers of eco-evolutionary processes. The evolution of traits shaped by these processes depends on their genetic architecture, which remains poorly studied. Here, implementing a quantitative genetics approach using diallel crosses of the bulb mite, Rhizoglyphus robini, we investigated the genetic variance that underlies a sexually-selected weapon that is dimorphic among males and female fecundity. Previous studies indicated that a negative genetic correlation between these two traits likely exists. We found male morph showed considerable additive genetic variance, which is unlikely to be explained solely by mutation-selection balance, indicating the likely presence of large-effect loci. However, a significant magnitude of inbreeding depression also indicates that morph expression is likely to be condition-dependent to some degree and that deleterious recessives can simultaneously contribute to morph expression. Female fecundity also showed a high degree of inbreeding depression, but variance in female fecundity was mostly explained by epistatic effects, with very little contribution from additive effects. We found no significant genetic correlation, nor any evidence for dominance reversal, between male morph and female fecundity. The complex genetic architecture underlying male morph and female fecundity in this system has important implications for our understanding of the evolutionary interplay between purifying selection and sexually antagonistic selection.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.011 |
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".