Determinants of R-loop formation at convergent bidirectionally transcribed trinucleotide repeats
Bibliographic record
Abstract
R-loops have been described at immunoglobulin class switch sequences, prokaryotic and mitochondrial replication origins, and disease-associated (CAG)n and (GAA)n trinucleotide repeats. The determinants of trinucleotide R-loop formation are unclear. Trinucleotide repeat expansions cause diseases including DM1 (CTG)n, SCA1 (CAG)n, FRAXA (CGG)n, FRAXE (CCG)n and FRDA (GAA)n. Bidirectional convergent transcription across these disease repeats can occur. We find R-loops formed when CTG or CGG and their complementary strands CAG or CCG were transcribed; GAA transcription, but not TTC, yielded R-loops. R-loop formation was sensitive to DNA supercoiling, repeat length, insensitive to repeat interruptions, and formed by extension of RNA:DNA hybrids in the RNA polymerase. R-loops arose by transcription in one direction followed by transcription in the opposite direction, and during simultaneous convergent bidirectional transcription of the same repeat forming double R-loop structures. Since each transcribed disease repeat formed R-loops suggests they may have biological functions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".