Molecular convergent and parallel evolution among four high-elevation anuran species from the Tibetan region
Bibliographic record
Abstract
BACKGROUND: To date, evidence for the relative prevalence or rarity of molecular convergent and parallel evolution is conflicting, and understanding of how these processes contribute to adaptation is limited. We compared four high-elevation anuran species (Bufo tibetanus, Nanorana parkeri, Rana kukunoris and Scutiger boulengeri) from the Tibetan region, and examined convergent and parallel amino acid substitutions between them and how they may have contributed to high-elevation adaptation. RESULTS: index was calculated and convergence/divergence correlation plotting was conducted. Furthermore, genes under positive selection and with elevated evolutionary rate were examined. We detected a large number of amino acid sites with convergent or parallel substitutions. Several pairs of high-elevation species, in particular, R. kukunoris vs N. parkeri and B. tibetanus vs S. boulengeri, had excessive amounts of convergent substitutions compared to neutral expectation. Nevertheless, these sites were mostly concentrated in a small number of genes (3-32), and no genome-wide convergence was detected. Furthermore, the majority of these convergent genes were neither under detectable positive selection nor had elevated evolutionary rates, although functional prediction analysis suggested some of the convergent genes could potentially contribute to high-elevation adaptation. CONCLUSIONS: There is a substantial amount of convergent evolution at the amino-acid level among high-elevation amphibians, although these sites are concentrated in a few genes, not widespread across the genomes. This may attribute to the fact that all the target species are from the same environment. The relative prevalence of convergent substitutions among high-elevation amphibians provides an excellent opportunity for further study of molecular convergent evolution.
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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) | 0.002 | 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".