Gene expression variations in high-altitude adaptation: a case study of the Asiatic toad (Bufo gargarizans)
Bibliographic record
Abstract
BACKGROUND: Genome-wide investigation of molecular mechanisms for high-altitude adaptation has attracted great attention in the last few years. In order to understand the contribution of gene expression level variations to high-altitude adaptation in Asiatic toads (Bufo gargarizans), we implemented a reciprocal transplant experiment between low- and high-altitude sites and sequenced 12 transcriptomes from brain, heart, and liver tissues. RESULTS: A large number of genes with expression differences (DEGs) between high- and low-altitude individuals (193 fixed and 844 plastic) were identified, and the majority of them were tissue specific. Heart displayed the largest number of DEGs, both plastic and fixed. Fixed DEGs were particularly concentrated in functions associated with muscle contraction, and the majority of them were down-regulated in high-altitude individuals. Plastic DEGs were highly concentrated in several energy metabolism related functional categories, and the majority of them were also down-regulated at high-altitude environments. In liver samples, genes associated with nutrient metabolism experienced a broad-scale expression down-regulation in high-altitude toads. CONCLUSIONS: These broadly suppressed expression patterns at high altitudes are in strong contrast to those of endothermic homeotherms, suggesting poikilothermic vertebrates may have adopted different strategies at high altitudes. Our results strongly support that both genotypic specialization and phenotypic plasticity play crucial role in adaptation to high altitude for Asiatic toads. Poikilothermic vertebrates are among the most hypoxia-tolerant animals known, and many molecular mechanisms remain elusive. We hope that our results will provide useful directions for future research.
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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 | 0.001 | 0.000 |
| 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".