Functional divergence of TBP homologs through distinct DNA binding dynamics
Bibliographic record
Abstract
Abstract The TATA box-binding protein (TBP) is an evolutionarily conserved basal transcription factor common in the pre-initiation complex of all three eukaryotic RNA polymerases (RNA Pols). Despite their high conservation, homologous TBPs exhibit species- and tissue-specific functions that may contribute to the increasingly complex gene expression regulation across evolutionary time. To determine the molecular mechanisms of species- and tissue-specificity for homologous TBPs, we examined the ability of yeast TBP and murine TBP paralogs to replace the endogenous TBP in mouse embryonic stem cells. We show that, despite the high conservation in the DNA binding domain among the homologs, they cannot fully rescue the lethality of TBP depletion in mESCs, largely due to their inability to support RNA Pol III transcription. Furthermore, we show that the homologs differentially support stress-induced transcription reprogramming, with the divergent N-terminal domain playing a role in modulating changes in transcriptional response. Lastly, we show that the homologs have vastly different DNA binding dynamics, suggesting a potential mechanism for the distinct functional behavior observed among the homologs. Taken together, these data show a remarkable balance between flexibility and essentiality for the different functions of homologous TBP in eukaryotic transcription.
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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".