New scoring system to identify RNA G-quadruplex folding
Bibliographic record
Abstract
G-quadruplexes (G4s) are non-canonical structures involved in many important cellular processes. To date, the prediction of potential G-quadruplex structures (PG4s) has been based almost exclusively on the sequence of interest agreeing with the algorithm Gx-N-1-7-Gx-N1-7-Gx-N1-7-Gx (where x ≥ 3 and N = A, U, G or C). However, many sequences agreeing with this algorithm do not form G4s and are considered false-positive predictions. Here we show the RNA PG4 candidate in the 3'-untranslated region (UTR) of the TTYH1 gene to be one such false positive. Specifically, G4 folding was observed to be inhibited by the presence of multiple-cytosine tracks, located in the candidate's genomic context, that adopted a Watson-Crick base-paired structure. Clearly, the neighbouring sequences of a PG4 may influence its folding. The secondary structure of 12 PG4 motifs along with either 15 or 50 nucleotides of their upstream and downstream genomic contexts were evaluated by in-line probing. Data permitted the development of a scoring system for the prediction of PG4s taking into account the effect of the neighbouring sequences. The accuracy of this scoring system was assessed by probing 14 other novel PG4 candidates retrieved in human 5'-UTRs. This new scoring system can be used, in combination with the standard algorithm, to better predict the folding of RNA G4s.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".