High-throughput RNA structure probing reveals critical folding events during early 60S ribosome assembly in yeast
Bibliographic record
Abstract
While the protein composition of various yeast 60S ribosomal subunit assembly intermediates has been studied in detail, little is known about ribosomal RNA (rRNA) structural rearrangements that take place during early 60S assembly steps. Using a high-throughput RNA structure probing method, we provide nucleotide resolution insights into rRNA structural rearrangements during nucleolar 60S assembly. Our results suggest that many rRNA-folding steps, such as folding of 5.8S rRNA, occur at a very specific stage of assembly, and propose that downstream nuclear assembly events can only continue once 5.8S folding has been completed. Our maps of nucleotide flexibility enable making predictions about the establishment of protein-rRNA interactions, providing intriguing insights into the temporal order of protein-rRNA as well as long-range inter-domain rRNA interactions. These data argue that many distant domains in the rRNA can assemble simultaneously during early 60S assembly and underscore the enormous complexity of 60S synthesis.Ribosome biogenesis is a dynamic process that involves the ordered assembly of ribosomal proteins and numerous RNA structural rearrangements. Here the authors apply ChemModSeq, a high-throughput RNA structure probing method, to quantitatively measure changes in RNA flexibility during the nucleolar stages of 60S assembly in yeast.
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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) | 0.000 | 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 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".