Author response: PHF13 is a molecular reader and transcriptional co-regulator of H3K4me2/3
Bibliographic record
Abstract
In human and other eukaryotic cells, DNA is packaged around proteins called histones to form a structure known as chromatin. Chemical tags added to the histones alter how the DNA is packaged and the activity of the genes encoded by that DNA. For example, many active genes are packaged around histone H3 proteins that have “Lysine 4 tri-methyl” tags attached to them. Another protein that is associated with chromatin is called PHF13 and it has several roles, including repairing damaged DNA. However, it was not known whether PHF13 binds to chromatin via the chemical tags, or in another way. Ho-Ryun, Xu, Fuchs et al. used several biochemical techniques in mouse and human cells to explore how PHF13 specifically interacts with chromatin. These experiments showed that PHF13 binds specifically to DNA and to two types of methyl tags (lysine 4-tri-methyl or lysine 4-di-methyl). These chemical tags are predominantly found at active promoters as well as at a small subset of less active promoters known as bivalent promoters. PHF13 interacted with other proteins on the chromatin that are known to either drive or repress gene activity and it’s depletion affected the activity of many genes. Whether PHF13 increased or decreased gene activity depended on whether it was bound to active or bivalent promoters. The active promoters targeted by PHF13 had higher numbers of the tri-methyl tags whereas the di-methyl tags were more common on the bivalent promoters. These findings provide preliminary evidence that a protein binding to different methyl tags in the same place on histone H3 can have opposite effects on gene activity. Ho-Ryun, Xu, Fuchs et al. now intend to find out more about the other proteins that interact with PHF13 on chromatin.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.447 | 0.232 |
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".