Toward understanding the genetic basis of adaptation to high-elevation life in poikilothermic species: A comparative transcriptomic analysis of two ranid frogs, Rana chensinensis and R. kukunoris
Bibliographic record
Abstract
BACKGROUND: Understanding how organisms adapt to high-elevation environments at a genome scale provides novel insights into the process of adaptive evolution. Previous studies have mainly focused on endothermic organisms, while poikilothermic species may have evolved different mechanisms to cope with high-elevation environments. In this context, we sequenced transcriptomes of a pair of closely related anuran species, Rana chensinensis and R. kukunoris, which inhabit respective low- and high-elevation habitats. By comparing the two transcriptomes, we identified candidate genes that may be involved in high-elevation adaption in poikilothermic species. RESULTS: Over 66 million sequence reads from each transcriptome were generated. A total of 41,858 and 39,293 transcripts for each species were obtained by de novo assembly. By comparing the orthologous transcripts, we identified 125 protein-coding genes that have likely experienced strong positive selection (Ka/Ks>1). In addition, 335 genes that may bear a signature of positive selection (1≥Ka/Ks>0.5) were also recognized. By considering their functions, fourteen candidate genes were determined to be likely involved in high-elevation adaptation, including two CYP genes, USP-1, and several others. CONCLUSIONS: We identified a set of candidate genes that may have promoted adaptation of R. kukunoris to its high-elevation environment. These include several genes that have previously been associated with oxygen binding, response to UV radiation, and repair of free radical injury. Detailed molecular, physiological, and phenotypic studies are required to better understand the roles of these genes in improving the performance of R. kukunoris in a high-elevation environment. We have evidence for both convergent and divergent evolution between endothermic and poikilothemic species, but additional research across a wide range of organisms will be necessary to comprehend the complexity of high-elevation adaptation.
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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 | 0.001 |
| 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) | 0.000 | 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".