Widespread dysregulation of mRNA splicing implicates RNA processing in the development and progression of Huntington’s disease
Bibliographic record
Abstract
ABSTRACT In Huntington’s disease (HD), a CAG repeat expansion mutation in the HTT gene drives a gain-of-function toxicity that disrupts mRNA processing. Although widespread dysregulation of gene splicing in the striatum has been shown in human HD post-mortem brain tissue, post-mortem analyses are likely confounded by cell type composition changes due to neuronal loss and astrogliosis in late stage HD. This limits the ability to identify dysregulation related to early pathogenesis. To study alternative splicing changes in early HD, we performed RNA-sequencing analysis in an established isogenic HD neuronal cell model. We report cell type-associated and CAG length-dependent splicing changes, and find an enrichment of RNA processing genes coupled with neuronal function-related genes showing mutant HTT -associated splicing changes. Comparison with post-mortem data also identified splicing events associated with early pathogenesis that persist to later stages of disease. In summary, our results highlight splicing dysregulation in RNA processing genes in early and late-stage HD, which may lead to disrupted neuronal function and neuropathology.
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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".