DNase-seq predicts regions of rotational nucleosome stability across diverse human cell types
Bibliographic record
Abstract
DNase-seq is primarily used to identify nucleosome-depleted DNase I hypersensitive (DHS) sites genome-wide that correspond to active regulatory elements. However, ≈ 40 yr ago it was demonstrated that DNase I also digests with a ≈ 10-bp periodicity around nucleosomes matching the exposure of the DNA minor groove as it wraps around histones. Here, we use DNase-seq data from 49 samples representing diverse cell types to reveal this digestion pattern at individual loci and predict genomic locations where nucleosome rotational positioning, the orientation of DNA with respect to the histone surface, is stably maintained. We call these regions DNase I annotated regions of nucleosome stability (DARNS). Compared to MNase-seq experiments, we show DARNS correspond well to annotated nucleosomes. Interestingly, many DARNS are positioned over only one side of annotated nucleosomes, suggesting that the periodic digestion pattern attenuates over the nucleosome dyad. DARNS reproduce the arrangement of nucleosomes around transcription start sites and are depleted at ubiquitous DHS sites. We also generated DARNS from multiple lymphoblast cell line (LCL) samples. We found that LCL DARNS were enriched at DHS sites present in most of the original 49 samples but absent in LCLs, while multi-cell-type DARNS were enriched at LCL-specific DHS sites. This indicates that variably open DHS sites are often occupied by rotationally stable nucleosomes in cell types where the DHS site is closed. DARNS provide additional information about precise DNA orientation within individual nucleosomes not available from other nucleosome positioning assays and contribute to understanding the role of chromatin in gene regulation.
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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".