Sexual dimorphism and heightened conditional expression in a sexually selected weapon in the Asian rhinoceros beetle
Bibliographic record
Abstract
Among the most dramatic examples of sexual selection are the weapons used in battles between rival males over access to females. As with ornaments of female choice, the most "exaggerated" sexually selected weapons vary from male to male more widely than other body parts (hypervariability), and their growth tends to be more sensitive to nutritional state or physiological condition compared with growth of other body parts ("heightened" conditional expression). Here, we use RNAseq analysis to build on recent work exploring these mechanisms in the exaggerated weapons of beetles, by examining patterns of differential gene expression in exaggerated (head and thorax horns) and non-exaggerated (wings, genitalia) traits in the Asian rhinoceros beetle, Trypoxylus dichotomus. Our results suggest that sexually dimorphic expression of weaponry involves large-scale changes in gene expression, relative to other traits, while nutrition-driven changes in gene expression in these same weapons are less pronounced. However, although fewer genes overall were differentially expressed in high- vs. low-nutrition individuals, the number of differentially expressed genes varied predictably according to a trait's degree of condition dependence (head horn > thorax horn > wings > genitalia). Finally, we observed a high degree of similarity in direction of effects (vectors) for subsets of differentially expressed genes across both sexually dimorphic and nutritionally responsive growth. Our results are consistent with a common set of mechanisms governing sexual size dimorphism and condition dependence.
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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".