An atlas of chromatin accessibility in the adult human brain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
regulatory elements (CREs), including promoters and enhancers. Within each cell, chromatin is arranged in specific patterns to expose the repertoire of CREs required for optimal spatiotemporal regulation of gene expression. To further understand the complex mechanisms that modulate transcription in the brain, we used frozen postmortem samples to generate the largest human brain and cell-type-specific open chromatin data set to date. Using the Assay for Transposase Accessible Chromatin followed by sequencing (ATAC-seq), we created maps of chromatin accessibility in two cell types (neurons and non-neurons) across 14 distinct brain regions of five individuals. Chromatin structure varies markedly by cell type, with neuronal chromatin displaying higher regional variability than that of non-neurons. Among our findings is an open chromatin region (OCR) specific to neurons of the striatum. When placed in the mouse, a human sequence derived from this OCR recapitulates the cell type and regional expression pattern predicted by our ATAC-seq experiments. Furthermore, differentially accessible chromatin overlaps with the genetic architecture of neuropsychiatric traits and identifies differences in molecular pathways and biological functions. By leveraging transcription factor binding analysis, we identify protein-coding and long noncoding RNAs (lncRNAs) with cell-type and brain region specificity. Our data provide a valuable resource to the research community and we provide this human brain chromatin accessibility atlas as an online database "Brain Open Chromatin Atlas (BOCA)" to facilitate interpretation.
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.
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 | 0.002 | 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 | 0.001 | 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 it