Repetitive DNA loci and their modulation by the non-canonical nucleic acid structures R-loops and G-quadruplexes
Bibliographic record
Abstract
Cells have evolved intricate mechanisms to maintain genome stability despite allowing mutational changes to drive evolutionary adaptation. Repetitive DNA sequences, which represent the bulk of most genomes, are a major threat to genome stability often driving chromosome rearrangements and disease. The major source of repetitive DNA sequences and thus the most vulnerable constituents of the genome are the rDNA (rDNA) repeats, telomeres, and transposable elements. Maintaining the stability of these loci is critical to overall cellular fitness and lifespan. Therefore, cells have evolved mechanisms to regulate rDNA copy number, telomere length and transposon activity, as well as DNA repair at these loci. In addition, non-canonical structure-forming DNA motifs can also modulate the function of these repetitive DNA loci by impacting their transcription, replication, and stability. Here, we discuss key mechanisms that maintain rDNA repeats, telomeres, and transposons in yeast and human before highlighting emerging roles for non-canonical DNA structures at these repetitive loci.
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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 | 0.001 |
| 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 | 0.000 |
| 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".