Telomeric i-motifs and C-strands inhibit parallel G-quadruplex extension by telomerase
Bibliographic record
Abstract
Telomeric C-rich repeated DNA sequences fold into tetrahelical i-motif structures in vitro at acidic pH. While studies have suggested that i-motifs may form in cells, little is known about their potential role in human telomere biology. In this study, we explore the effect of telomeric C-strands and i-motifs on the ability of human telomerase to extend G-rich substrates. To promote i-motif formation at neutral pH, we use telomeric sequences where the cytidines have been substituted with 2'-fluoroarabinocytidine. Using FRET-based studies, we show that the stabilized i-motifs resist hybridization to concomitant parallel G-quadruplexes, implying that both structures could exist simultaneously at telomeric termini. Moreover, through telomerase activity assays, we show that both unstructured telomeric C-strands and telomeric i-motifs can inhibit the activity and processivity of telomerase extension of parallel G-quadruplexes and linear telomeric DNA. The data suggest at least three modes of inhibition by C-strands and i-motifs: direct hybridization to the substrate DNA, hybridization to nascent product DNA resulting in early telomerase dissociation, and interference with the unique mechanism of telomerase unwinding and extension of a G-quadruplex. Overall, this study highlights a potential inhibitory role for the telomeric C-strand in telomere maintenance.
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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) | 0.001 | 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 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".