ATAC-Seq of a Single Myofiber from Mus musculus
Bibliographic record
Abstract
Chromatin accessibility is a key determinant of gene expression that can be altered under different physiological and disease conditions. Skeletal muscle is made up of myofibers that are highly plastic and adaptive. Therefore, assessing the genome-wide chromatin state of myofibers under various conditions is very important to gain insight into the epigenetic state of myonuclei. The rigid nature of myofibers, as well as the low number of myonuclei that they contain, have rendered genome-wide studies with myofibers challenging. In recent years, ATAC-Seq from whole muscle and single nucleus ATAC-Seq have been performed. However, these techniques cannot distinguish between different fiber and cell types present in the muscle. In addition, due to the limited depth capacity obtained from single nucleus ATAC-Seq, an extensive comparative analysis cannot be performed. Here, we introduce a protocol where we combine the isolation of a single myofiber with OMNI ATAC-Seq. This protocol allows for genome-wide analysis of accessible chromatin regions of a selected single myofiber at a sufficient depth for comparative analysis under various physiological and disease conditions. This protocol can also allow for a specific myofiber to be selected, such as a regenerating myofiber. In the future, this protocol can help identify global changes in chromatin state under various conditions, as well as between different types of myofibers. Graphical abstract.
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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) | 0.001 | 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 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".