Divergent Cardiovascular Adaptations and Gene Regulation in High-Elevation Natives and Recent Colonizers of the Qinghai-Tibetan Plateau
Bibliographic record
Abstract
High elevation imposes unrelenting and unavoidable hypoxia on species inhabiting these environments, providing an excellent natural setting for studying convergent or divergent evolution. By integrating measures of phenotypic variation, gene regulation, and functional performance, our study demonstrates that recent colonizers of high-elevation environments exhibit fundamentally different cardiovascular changes compared to long-term natives of these environments. Through the studying of heart morphological phenotypes, we showed that recent colonizers exhibit signs of cardiac hypertrophy, reflected by increased relative heart mass (heart mass/body mass) and cardiomyocyte size compared to their low-elevation relatives. In contrast, native species show no signs of cardiac hypertrophy and instead have 3-fold higher capillary densities than the colonizers, a change that likely enhances tissue oxygen diffusing capacity in the former. Using phylogenetic principal component analysis to quantify multivariate trait divergence, we show that native species are similar in cardiovascular phenotype and underlying gene expression, but differ appreciably from recent colonizers. We further demonstrate, using a functional assay, that differential expression of two genes (IRS2 and AKT1) in a conserved regulatory pathway mediates cardiomyocyte hypertrophy, which could explain the observed variation in cardiomyocyte size between native species and recent colonizers. This regulatory basis of variation in cardiac phenotype involves the differential expression of genes in a cardiomyocyte hypertrophy pathway that is conserved across birds, humans and other mammals. Collectively, our study highlights that evolutionary history is a critical determinant of cardiovascular variation in high-elevation environments.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".