Passive diffusion through nuclear pore complexes regulates levels of the yeast SAGA and SLIK coactivators complexes
Bibliographic record
Abstract
Abstract Nuclear pore complexes (NPCs) control gene expression by regulating the bi-directional exchange of proteins and RNAs between nuclear and cytoplasmic compartments, including access of transcriptional regulators to the nucleoplasm. Here we show that the yeast nucleoporin Nup170, in addition to binding and silencing subtelomeric genes, supports transcription of genes regulated by the SAGA transcriptional activator. Specifically, we show that less SAGA complex is bound to target genes in the absence Nup170. Consistent with this observation, levels of the SAGA complex are decreased in cells lacking Nup170, while SAGA-related SLIK complexes are increased. This change in the ratio of SAGA to SLIK complexes is due to increased nuclear activity of Pep4, a protease responsible for production of the SLIK complex. Further analyses of various nucleoporin mutants revealed that the increased nuclear entry of Pep4 observed in the nup170 Δ mutant likely occurs as consequence of an increase in the sieving limits of the NPC diffusion channel. On the basis of these results, we propose that changes in passive diffusion rates represents a mechanism for regulating SAGA/SLIK complex-mediated transcriptional events.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".