The Disease-associated r(GGGGCC) Repeat from the C9orf72 Gene Forms Tract Length-dependent Uni- and Multimolecular RNA G-quadruplex Structures
Bibliographic record
Abstract
Certain DNA and RNA sequences can form G-quadruplexes, which can affect promoter activity, genetic instability, RNA splicing, translation, and neurite mRNA localization. Amyotrophic lateral sclerosis and frontotemporal dementia were recently shown to be caused by expansion of a (GGGGCC)n·(GGCCCC)n repeat in the C9orf72 gene. Mutant r(GGGGCC)n-containing transcripts aggregate in nuclear foci possibly sequestering repeat-binding proteins, suggesting a toxic RNA pathogenesis. We demonstrate that the r(GGGGCC)n RNA but not the C-rich r(GGCCCC)n RNA forms extremely stable uni- and multimolecular parallel G-quadruplex structures (up to 95 °C). Multimolecular G-quadruplex formation is influenced by repeat number and RNA concentration. MBNL1, a splicing factor that is sequestered in myotonic dystrophy patients by binding to expanded r(CUG)n repeat hairpins, does not bind the C9orf72 repeats, but the splicing factor ASF/SF2 can bind the r(GGGGCC)n repeat. Because multimolecular G-quadruplexes are enhanced by repeat length, RNA-RNA interactions facilitated by G-quadruplex formation at expanded repeats might influence transcript aggregation and foci formation in amyotrophic lateral sclerosis-frontotemporal dementia cells. Tract length-dependent G-quadruplex formation by the C9orf72 RNA should be considered when assessing the role of this repeat in C9orf72 gene activity, protein binding, transcript foci formation, and translation of the C9orf72 product, including the noncanonical repeat-associated non-ATG translation (RAN translation) into pathologic dipeptide repeats, as well as any oligonucleotide repeat-based therapy.
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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 | 0.001 |
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".