Identification of CCR4 and other essential thyroid hormone receptor co-activators by modified yeast synthetic genetic array analysis
Bibliographic record
Abstract
Identification of thyroid hormone receptor (TR) co-regulators has enhanced our understanding of thyroid hormone (TH) action. However, it is likely that many other co-regulators remained unidentified, and unbiased methods are required to discover these proteins. We have previously demonstrated that the yeast Saccharomyces cerevisiae is an excellent system in which to study TR action, and that defined TR signaling complexes in a eukaryotic background devoid of complicating influences of mammalian cell co-regulators can be constructed and analyzed for endogenous yeast genes, many of which are conserved in mammals. Here, a modified synthetic genetic array analysis was performed by crossing a yeast strain that expressed TRbeta1 and the co-activator GRIP1/SRC2 with 384 yeast strains bearing deletions of known genes. Eight genes essential for TH action were isolated, of which 4 are conserved in mammals. Examination of one, the yeast CCR4 and its human homolog CCR4/NOT6 (hCCR4), confirmed that (i) transfected CCR4 potentiates a TH response in cultured cells more efficiently than established TR co-activators and (ii) knockdown of CCR4 expression strongly inhibited a TH response (>80%). TH treatment promoted rapid and sustained hCCR4 recruitment to the TH-responsive deiodinase 1 promoter and TR co-localizes with hCCR4 in the nucleus and interacts with hCCR4 in 2-hybrid and pull-down assays. These findings indicate that a modified yeast synthetic genetic array strategy is a feasible method for unbiased identification of conserved genes essential for TR and other nuclear receptor hormone functions in mammals.
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 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) | 0.001 | 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 | 0.001 |
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".