Integration and coevolution of the mammalian skeleton in “real time”: the case of the Longshanks mouse
Bibliographic record
Abstract
Since the publication of Olson and Miller's seminal book “Morphological Integration” in 1958, there have been over 200 studies on integration, modularity and evolvability of the mammalian skeletal and dental systems. These studies have yielded fundamental insights into the role of genetic, developmental and functional constraints on the evolutionary history, and evolutionary potential, of complex skeletal traits in diverse mammalian lineages. Yet integration and evolvability studies in skeletal systems suffer from two important limitations. First, they are by nature post‐hoc, i.e., they rely on observed patterns of covariation among traits to reconstruct the (often deep) history of (co)evolution in skeletal traits, and/or to identify the genetic, developmental and functional sources of covariation that have influenced this history. Second, and related, evolvability studies are theoretical, relying on the multivariate breeder's equation to predict the potential response of more or less integrated skeletal phenotypes to selection. Since 2010, my lab has been selectively breeding mice for increases in tibia length relative to body mass. This long‐term selection experiment provides an opportunity to validate empirically how the magnitude and pattern of covariation among skeletal traits (i.e., integration) impacts “real time” evolutionary change in the target of selection, as well as in genetically and developmentally correlated traits. Here, I use an evolutionary quantitative genetics framework and a large multi‐generational dataset of full body micro‐CT scans of the selectively bred mice (Longshanks) and random‐bred mice to: (1) quantify correlated evolution of skeletal traits in the Longshanks postcranium and cranium, and (2) determine how the magnitude and pattern of integration across the skeleton has evolved in response to strong selection on a single trait. Results show that while tibia length has changed the most, other skeletal traits (e.g. tibia cross‐sectional shape, other fore‐ and hind limb bone lengths) have also responded to selection, though to a lesser extent (i.e., allometrically). Interestingly, skull shape in Longshanks has changed significantly. The types of changes observed over ontogeny suggest the involvement of both local and systemic factors underlying mechanisms of endochondral ossification in the limbs and cranial base. Finally, the magnitude of covariation among postcranial skeletal traits increased over generations, which suggests that unidirectional selection on a single skeletal trait in Longshanks has actually reduced the evolvability of its skeleton overall. This study in “real time” vertebrate evolution thus validates and complements the insights gleaned from classical, yet largely theoretical, integration, modularity and evolvability in the mammalian skeleton. Support or Funding Information This work was supported by NSERC Discovery Grant 4181932, and by the Faculty of Veterinary Medicine at the University of Calgary.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".