Altered huntingtin−chromatin interactions predict transcriptional and epigenetic changes in Huntington's disease
Bibliographic record
Abstract
While progressive striatal gene expression changes and epigenetic alterations are a prominent feature of Huntington's disease (HD), the mechanistic basis remains poorly understood. Using chromatin immunoprecipitation and sequencing (ChIP-seq), we show that the huntingtin protein (HTT) reproducibly occupies specific locations in the mouse genome. Striatal HTT ChIP-seq peaks were enriched in coding regions of spiny projection neuron identity genes that were found to have reduced expression in HD patients and mouse models, and had reduced occupancy in expanded polyglutamine HTT knock-in mice (HttQ111/Q111). By contrast, HTT occupancy was depleted near genes that are upregulated in HD. ChIP-seq of striatal histone modifications revealed genotype-specific colocalization of HTT with active chromatin marks and enhancer of zeste homolog 2 (EZH2), a key enzymatic component of the PRC2 complex. In the vicinity of genes that are differentially regulated in HD, greater HTT occupancy in HttQ111/Q111 vs wild-type mice was associated with increased EZH2 occupancy, increased H3K4me3 levels and decreased H3K27me3 levels. Our study suggests that HTT-chromatin interactions may play a role in organizing chromatin and promoting cell type-specific gene expression, with HTT occupancy predicting transcriptional dysregulation in HD.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".