Synergistic interaction network between the snR30 RNP, Utp23, and ribosomal RNA during ribosome synthesis
Bibliographic record
Abstract
snR30/U17 is a highly conserved H/ACA RNA that is required for maturation of the small ribosomal subunit in eukaryotes. By base-pairing to the expansion segment 6 (ES6) of 18S ribosomal RNA (rRNA), the snR30 H/ACA Ribonucleoprotein (RNP) indirectly facilitates processing of the precursor rRNA (pre-rRNA) together with other proteins such as Utp23 and other RNAs acting as ribosome assembly factors. However, the details of the molecular interaction network of snR30 and its binding partners and how these interactions contribute to pre-rRNA processing remains unknown. Here, we report the in vitro reconstitution of a Saccharomyces cerevisiae snR30 RNP and quantitative characterization of the interactions of snR30, H/ACA proteins, the Utp23 protein and ES6 of the 18S rRNA. The snR30 RNA is bound tightly by both H/ACA proteins and Utp23. We dissected the importance of different 18S rRNA regions for snR30 RNP binding and demonstrated that the snR30 complex is tightly anchored on the pre-rRNA through base-pairing to ES6 whereas other reported rRNA binding sites do not contribute to the affinity of the snR30 RNP. On its own, the ribosome assembly factor Utp23 binds in a tight, but unspecific manner to RNA. However, in complex with the snR30 RNP, Utp23 increases the affinity of the RNP for rRNA revealing synergies between snR30 RNP and Utp23 which are enhancing specificity and affinity for rRNA, respectively. Together, these findings provide mechanistic insights how the snR30 RNP and Utp23 cooperate to interact tightly and specifically with rRNA during the early stages of ribosome biogenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".