Analysis of convergent and parallel amino acid substitutions in the HSP90AA1 gene among high-elevation anurans
Bibliographic record
Abstract
A significant amount of convergent and parallel amino acid substitutions in the HSP90AA1 gene has been detected among four species of high-elevation anurans: Bufo tibetanus, Scutiger boulengeri, Rana kukunoris, and Nanorana parkeri. As HSP proteins are involved in response to environmental stress, it is possible these mutations play a role in high-elevation adaptation. In this study, I investigated the functional consequences of these substitutions and inferred their potential links to adaptation. I examined HSP90AA1 sequences of 13 anuran species previously studied. Using PROVEAN, I isolated three deleterious mutations: P65S, K195A, and _199I, each shared between two of the high-elevation species. I further analyzed the protein structure, stability change, and structural damage using model predictions. Based on its buried location and cavity expansion, P65S was predicted to most likely alter protein function. Furthermore, I examined HSP90AA1 sequences of over 100 other animal species available from public databases and found that serine at site 65 is ubiquitously present in cold-water fish, suggesting the substitution is related to cold adaptation. Alanine at site 195 and isoleucine at site 199 were not found in any other species, but these substitutions also might impact protein function as they are predicted to be destabilizing and their ancestral residues have reported post-translational modifications in orthologs. Tests of protein function and an investigation of more sequences from high-elevation species would help to further link these substitutions to adaptation, particularly P65S. Identifying mutations that contribute to high-elevation adaptation would aid in uncovering the molecular mechanisms of adaptation.
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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 | 0.000 |
| 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".