Adaptive tail-length evolution in deer mice is associated with differential Hoxd13 expression in early development
Bibliographic record
Abstract
Variation in the size and number of axial segments underlies much of the diversity in animal body plans. Here we investigate the evolutionary, genetic and developmental mechanisms driving tail-length differences between forest and prairie ecotypes of deer mice (Peromyscus maniculatus). We first show that long-tailed forest mice perform better in an arboreal locomotion assay, consistent with tails being important for balance during climbing. We then identify six genomic regions that contribute to differences in tail length, three of which associate with caudal vertebra length and the other three with vertebra number. For all six loci, the forest allele increases tail length, indicative of the cumulative effect of natural selection. Two of the genomic regions associated with variation in vertebra number contain Hox gene clusters. Of those, we find an allele-specific decrease in Hoxd13 expression in the embryonic tail bud of long-tailed forest mice, consistent with its role in axial elongation. Additionally, we find that forest embryos have more presomitic mesoderm than prairie embryos and that this correlates with an increase in the number of neuromesodermal progenitors, which are modulated by Hox13 paralogues. Together, these results suggest a role for Hoxd13 in the development of natural variation in adaptive morphology on a microevolutionary timescale.
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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 | 0.001 | 0.001 |
| 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".