Genome-Wide Prediction and Analysis of Yeast RNase III-Dependent snoRNA Processing Signals
Bibliographic record
Abstract
In Saccharomyces cerevisiae, the maturation of both pre-rRNA and pre-small nucleolar RNAs (pre-snoRNAs) involves common factors, thereby providing a potential mechanism for the coregulation of snoRNA and rRNA synthesis. In this study, we examined the global impact of the double-stranded-RNA-specific RNase Rnt1p, which is required for pre-rRNA processing, on the maturation of all known snoRNAs. In silico searches for Rnt1p cleavage signals, and genome-wide analysis of the Rnt1p-dependent expression profile, identified seven new Rnt1p substrates. Interestingly, two of the newly identified Rnt1p-dependent snoRNAs, snR39 and snR59, are located in the introns of the ribosomal protein genes RPL7A and RPL7B. In vitro and in vivo experiments indicated that snR39 is normally processed from the lariat of RPL7A, suggesting that the expressions of RPL7A and snR39 are linked. In contrast, snR59 is produced by a direct cleavage of the RPL7B pre-mRNA, indicating that a single pre-mRNA transcript cannot be spliced to produce a mature RPL7B mRNA and processed by Rnt1p to produce a mature snR59 simultaneously. The results presented here reveal a new role of yeast RNase III in the processing of intron-encoded snoRNAs that permits independent regulation of the host mRNA and its associated snoRNA.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".