A Polymorphic Autoregulatory Hormone Response Element in the Human Estrogen-related Receptor α (ERRα) Promoter Dictates Peroxisome Proliferator-activated Receptor γ Coactivator-1α Control of ERRα Expression
Bibliographic record
Abstract
The orphan nuclear estrogen-related receptor alpha (ERRalpha) and transcriptional cofactor peroxisome proliferator-activated receptor gamma coactivator-1alpha (PGC-1alpha) are involved in the regulation of energy metabolism. Recently, extensive cross-talk between PGC-1alpha and ERRalpha has been demonstrated. The presence of PGC-1alpha is associated with an elevated expression of ERRalpha, and the two proteins can influence the transcriptional activities of one another. Using a candidate gene approach to detect regulatory variants within genes encoding nuclear receptors, we have identified a 23-bp sequence (ESRRA23) containing two nuclear receptor recognition half-site motifs that is present in 1-4 copies within the promoter of the human ESRRA gene encoding ERRalpha. The ESRRA23 sequence contains a functional ERR response element that is specifically bound by ERRalpha, and chromatin immunoprecipitation shows that endogenous ERRalpha occupies its own promoter in vivo. Strikingly, introduction of PGC-1alpha in HeLa cells by transient transfection induces the activity of the ESRRA promoter in a manner that is dependent on the presence of the ESRRA23 element and on its dosage. Coexpression of ERRalpha and PGC-1alpha results in a synergistic activation of the ESRRA promoter. In experiments using ERRalpha null fibroblasts, the ability of PGC-1alpha to stimulate the ESRRA promoter is considerably reduced but can be restored by addition of ERRalpha. Taken together, these results demonstrate that an interdependent ERRalpha/PGC-1alpha-based transcriptional pathway targets the ESRRA23 element to dictate the level of ERRalpha expression. This study further suggests that this regulatory polymorphism may provide differential responses to ERRalpha/PGC-1alpha-mediated metabolic cues in the human population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".