Epigenetic Effects on Integration of Limb Lengths in a Mouse Model: Selective Breeding for High Voluntary Locomotor Activity
Bibliographic record
Abstract
Mammals exhibit a similar pattern of integration among homologous limb elements, the strength of which is believed to vary in response to selection for functional coordination or similarity. Although integration is hypothesized to primarily reflect the effect of genes intrinsic to limbs, extrinsic genetic or epigenetic factors may also affect the strength of integration through their impact on the magnitude and direction of skeletal variance or covariance. Such factors as neuromuscular coordination or bone-muscle interactions may therefore play a role in both canalization and the structure or magnitude of limb integration. If this were the case, then increased levels of locomotor activity would be predicted to increase canalization and the magnitude of covariation between limbs. To investigate whether postnatal activity levels can have a significant effect on variance within or covariance among homologous limb elements, we compared four groups of male mice from a long-term selective breeding experiment: (1) mice from lines bred for increased voluntary activity on running wheels and allowed free access to a wheel for 8 weeks beginning at weaning (“active”), (2) selected mice that did not have wheel access (“sedentary”), (3) active mice from non-selected control lines, and (4) sedentary control mice. Mice from selected lines that had wheel access ran significantly more than control-line mice. However, when controlled for activity, linetype, and body mass, results indicate few significant differences in means, variance, or covariation structure, and no significant differences in integration between limbs, suggesting that postnatal activity levels do not significantly affect canalization or integration of limb lengths. A possible explanation for this result is that whereas baseline levels of postnatal activity may help to maintain patterns of variance and integration, increased levels of activity do not further increase these measures. Investigations into disrupted epigenetic processes (e.g., via models in which neuromuscular coordination is impaired) are required to further test hypotheses about how canalization or integration of limb variation is affected by epigenetic factors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".