Species groups distributed across elevational gradients reveal convergent and continuous genetic adaptation to high elevations
Bibliographic record
Abstract
Although many cases of genetic adaptations to high elevations have been reported, the processes driving these modifications and the pace of their evolution remain unclear. Many high-elevation adaptations (HEAs) are thought to have arisen in situ as populations rose with growing mountains. In contrast, most high-elevation lineages of the Qinghai-Tibetan Plateau appear to have colonized from low-elevation areas. These lineages provide an opportunity for studying recent HEAs and comparing them with ancestral low-elevation alternatives. Herein, we compare four frogs (three species of Nanorana and a close lowland relative) and four lizards ( Phrynocephalus ) that inhabit a range of elevations on or along the slopes of the Qinghai-Tibetan Plateau. The sequential cladogenesis of these species across an elevational gradient allows us to examine the gradual accumulation of HEA at increasing elevations. Many adaptations to high elevations appear to arise gradually and evolve continuously with increasing elevational distributions. Numerous related functions, especially DNA repair and energy metabolism pathways, exhibit rapid change and continuous positive selection with increasing elevations. Although the two studied genera are distantly related, they exhibit numerous convergent evolutionary changes, especially at the functional level. This functional convergence appears to be more extensive than convergence at the individual gene level, although we found 32 homologous genes undergoing positive selection for change in both high-elevation groups. We argue that species groups distributed along a broad elevational gradient provide a more powerful system for testing adaptations to high-elevation environments compared with studies that compare only pairs of high-elevation versus low-elevation species.
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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 | 0.001 |
| 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".