Genetic signals of high-altitude adaptation in amphibians: a comparative transcriptome analysis
Bibliographic record
Abstract
High-altitude adaptation provides an excellent system for studying how organisms cope with multiple environmental stressors and interacting genetic modifications. To explore the genetic basis of high-altitude adaptation in poikilothermic animals, we acquired transcriptome sequences from a high-altitude population and a low-altitude population of the Asiatic toad ( Bufo gargarizans ). Transcriptome data from another high-altitude amphibian, Rana kukunoris and its low-altitude relative R. chensiensis , which are from a previous study, were also incorporated into our comparative analysis. More than 40,000 transcripts were obtained from each transcriptome, and 5107 one-to-one orthologs were identified among the four taxa for comparative analysis. A total of 29 ( Bufo ) and 33 ( Rana ) putative positively selected genes were identified for the two high-altitude species, which were mainly concentrated in nutrient metabolism related functions. Using SNP-tagging and F ST outlier analysis, we further tested 89 other nutrient metabolism related genes for signatures of natural selection, and found that two genes, CAPN2 and ITPR1, were likely under balancing selection. We did not detect any positively selected genes associated with response to hypoxia . Amphibians clearly employ different genetic mechanisms for high-altitude adaptation compared to endotherms. Modifications of genes associated with nutrient metabolism feature prominently while genes related to hypoxia tolerance appear to be insignificant. Poikilotherms represent the majority of animal diversity, and we hope that our results will provide useful directions for future studies of amphibians as well as other poikilotherms.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".