A Functional Interface at the rDNA Connects rRNA Synthesis, Pre-rRNA Processing and Nucleolar Surveillance in Budding Yeast
Bibliographic record
Abstract
Ribogenesis is a multistep error-prone process that is actively monitored by quality control mechanisms. How ribosomal RNA synthesis, pre-rRNA processing and nucleolar surveillance are integrated is unclear. Nor is it understood how defective ribosomes are recognized. We report in budding yeast that, in vivo, the interaction between the transcription elongation factor Spt5 and Rpa190, the largest subunit of RNA polymerase (Pol) I, requires the Spt5 C-terminal region (CTR), a conserved and highly repetitive domain that is reminiscent of the RNA Pol II C-terminal domain (CTD). We show that this sequence is also required for the interaction between Spt5 and Nrd1, an RNA specific binding protein, and an exosome cofactor. Both the Spt4-Spt5, and the Nrd1-Nab3 complexes interact functionally with Rrp6, and colocalize at the rDNA. Mutations in the RNA binding domain of Nrd1, but not in its RNA Pol II CTD-interacting domain, and mutations in the RRM of Nab3 led to the accumulation of normal and aberrant polyadenylated pre-rRNAs. Altogether these results indicate that Nrd1-Nab3 contributes to recruiting the nucleolar surveillance to elongating polymerases to survey nascent rRNA transcripts.
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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 | 0.000 |
| 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".