Longevity and environmental temperature modulate mitochondrial DNA evolution in fishes
Bibliographic record
Abstract
Abstract The link between longevity and mitochondrial function has been documented for years. Since mitochondrial DNA (mtDNA) encodes for electron transport system (ETS) proteins, we could suspect that its evolution is linked with that of longevity. A negative relationship has been documented between the synonymous substitution rate and lifespan when analyzing the whole mitochondrial genome in animals. In this study, we aimed to confirm this negative correlation for each of the mitochondrial protein coding genes (mtPCGs) and explore potential relationships between adaptation to extreme temperatures and the evolution of mtDNA. To this end, we selected 112 species of fish with a wide range of longevity as well as divergences in environmental temperature, which is a good proxy for energy metabolism in these animals. Our results 1) challenge the “rate of living” theory by not showing any correlation between longevity and environmental temperature, 2) confirm the negative relationship between substitution rate and longevity for each of the 13 mtPCGs, and 3) highlight for the first time a link between high conservation of the three COX genes and adaptation to warmer temperatures in fish. By challenging a paradigm and extending the conclusions made for mtDNA to individual genes, our study opens a wide field to be explored concerning study of the aging process. Moreover, the specific link between the evolution of COX genes and temperature tolerance confirms the importance of complex IV in adaptation to extreme temperatures and, more generally, the importance of distinguishing gene families when studying mtDNA evolution in animals.
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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 | 0.000 |
| 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".