Bibliographic record
Abstract
A critical step in spliceosome assembly is the formation of the U4/U6 di-snRNP particle in which U4 and U6 snRNAs are engaged in an extensive intermolecular base pairing interaction. Little is known about how this particle is formed or its role in pre-mRNA splicing, and current models of U6 snRNA secondary structure in free U6 snRNP do not offer insight into these questions. We have generated a new model of U6 snRNA secondary structure in free U6 snRNP that is consistent with existing structural and genetic data. A key feature of our model is that a previously proposed 3' intramolecular stem/loop has been replaced with two stem/loops, one of which sequesters the functionally important ACAGAGA sequence. We show support for this model through genetic analyses as well as oligonucleotide accessibility experiments in which the ACAGAGA sequence was inaccessible to a complementary oligonucleotide. This observation is consistent with only our model since all other proposed models predict that this sequence resides in a large single-stranded region of the molecule and should therefore be accessible for efficient oligonucleotide annealing. Our model predicts that the ACAGAGA sequence is unavailable for interaction with the pre-mRNA transcript until a large structural re-arrangement exposes the sequence during early stages of spliceosome assembly. We propose that U4 snRNA is responsible for promoting the U6 snRNA structural re-arrangement, releasing the ACAGAGA sequence from the sequestering interaction through the establishment of an intermolecular interaction between U4 and U6 to generate the di-snRNP particle.
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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 | 0.001 |
| 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 | 0.001 | 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".