Sex-specific genetic (co)variances of standard metabolic rate, body mass and locomotor activity in Drosophila melanogaster
Bibliographic record
Abstract
A longstanding focus in evolutionary physiology concerns the causes and consequences of variation in maintenance metabolism. Insight into this can be gained by estimating the sex-specific genetic architecture of maintenance metabolism alongside other, potentially correlated traits on which selection may also act, such as body mass and locomotor activity. This may reveal potential genetic constraints affecting the evolution of maintenance metabolism. Here, we used a half-sibling breeding design to quantify the sex-specific patterns of genetic (co)variance in standard metabolic rate (SMR), body mass, and daily locomotor activity in Drosophila melanogaster. There was detectable additive genetic variance for all traits in both sexes. As expected, SMR and body mass were strongly and positively correlated, with genetic allometry exponents (bA±se) of 0.66±0.16 in females and 0.58±0.32 in males. There was a significant and positive genetic correlation between SMR and locomotor activity in males, suggesting that alleles that increase locomotion have pleiotropic effects on SMR. Sexual differences in the genetic architecture were driven in large part by a difference in genetic variance in locomotor activity between the sexes. Overall, genetic variation was mostly shared between males and females, setting the stage for a potential intralocus sexual conflict in the face of 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".