Comprehensive Transcriptome Analysis Reveals Accelerated Genic Evolution in a Tibet Fish, Gymnodiptychus pachycheilus
Bibliographic record
Abstract
Elucidating the genetic mechanisms of organismal adaptation to the Tibetan Plateau at a genomic scale can provide insights into the process of adaptive evolution. Many highland species have been investigated and various candidate genes that may be responsible for highland adaptation have been identified. However, we know little about the genomic basis of adaptation to Tibet in fishes. Here, we performed transcriptome sequencing of a schizothoracine fish (Gymnodiptychus pachycheilus) and used it to identify potential genetic mechanisms of highland adaptation. We obtained totally 66,105 assembled unigenes, of which 7,232 were assigned as putative one-to-one orthologs in zebrafish. Comparative gene annotations from several species indicated that at least 350 genes lost and 41 gained since the divergence between G. pachycheilus and zebrafish. An analysis of 6,324 orthologs among zebrafish, fugu, medaka, and spotted gar identified consistent evidence for genome-wide accelerated evolution in G. pachycheilus and only the terminal branch of G. pachycheilus had an elevated Ka/Ks ratio than the ancestral branch. Many functional categories related to hypoxia and energy metabolism exhibited rapid evolution in G. pachycheilus relative to zebrafish. Genes showing signature of rapid evolution and positive selection in the G. pachycheilus lineage were also enriched in functions associated with energy metabolism and hypoxia. The first genomic resources for fish in the Tibetan Plateau and evolutionary analyses provided some novel insights into highland adaptation in fishes and served as a foundation for future studies aiming to identify candidate genes underlying the genetic bases of adaptation to Tibet in fishes.
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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".