G-quadruplex structures as modulators of alternative promoter usage
Bibliographic record
Abstract
The precise regulation of gene transcription relies on promoters, and the selection of specific promoters for a particular gene is a key determinant of transcript diversity. However, the regulatory mechanisms governing promoter selection are not fully understood. G-quadruplexes (G4s) are unique DNA noncanonical secondary structures that have emerged as important regulators of gene expression. In this study, we systematically analyzed the relationship between G4 structures and alternative promoters (APs) in two cancer cell lines, K562 and HepG2, by integrating native elongating transcript-cap analysis of gene expression and G4 ChIP-seq datasets. We identified 573 differentially utilized APs (|fold change| > 2, false discovery rate < 0.05), 26% of which being associated with G4 structures within 100 base pairs. Notably, G4-associated promoters predominantly exhibited increased activity, suggesting that G4s generally promote AP selection. Furthermore, treatment with G4 ligands induced the generation of APs, suggesting that the stabilization of G4 structures may modulate AP usage. Collectively, these findings provide new insights into the G4-based mechanisms that regulate transcript isoform diversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".