Evolutionary and functional variation of PGC‐1α in vertebrates
Bibliographic record
Abstract
In mammals, PGC‐1α is a central regulator of oxidative metabolism through its interactions with NRF‐1 and the PPARs. We examined the role of PGC‐1α in the evolution and development of physiological variations in vertebrates’ oxidative capacity. First, we sought to determine the regulators of the temperature and dietary‐induced metabolic remodeling in goldfish. NRF‐1 and PPARα, respectively, had typical roles in orchestrating mitochondrial proliferation and fatty acid oxidation. In contrast, while goldfish PGC‐1α seemed to be involved in the regulation of the PPAR axis, it did not appear to play a role in NRF‐1 dependent mitochondrial proliferation. To assess the structural basis of these divergent roles in mammals and fish, we investigated the evolutionary trajectory of PGC‐1α in representative vertebrate lineages. The analysis revealed a good conservation of the activation/PPAR interaction domain across vertebrates, whereas the NRF‐1 interaction domain experienced accelerated rates of evolution in Actinopterygians (fish lineages) compared to Sarcopterygians (tetrapod lineages). Furthermore, protein sequence analysis of this variable domain in lineages giving rise to modern teleosts revealed successive serine and glutamine residues insertions with important functional repercussions on PGC‐1α control of mitochondrial proliferation in teleosts. Funded by NSERC (Canada).
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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 | 0.000 |
| 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".