Reciprocal regulation of chromatin state and architecture by<i>HOTAIRM1</i>contributes to temporal collinear<i>HOXA</i>gene activation
Bibliographic record
Abstract
Thousands of long non-coding RNAs (lncRNAs) have been identified in mammals, many of which represent important regulators of gene expression. However, the mechanisms used by lncRNAs to control transcription remain largely uncharacterized. Here, we report on HOTAIRM1, a promising lncRNA biomarker in leukemia and solid tumors. We find that HOTAIRM1 contributes to three-dimensional chromatin organization changes required for the temporal collinear activation of HOXA genes. We show that distinct HOTAIRM1 variants preferentially associate with either UTX/MLL or PRC2 complexes to modulate the levels of activating and silencing marks at the bivalent domain. HOTAIRM1 contributes to physical dissociation of chromatin loops at the cluster proximal end, which delays recruitment of the histone demethylase UTX and transcription of central HOXA genes. Interestingly, we find overall proximal HOXA gene activation without chromatin conformation changes by HOTAIRM1 in a different cell type. Our results reveal a previously unappreciated relationship between chromatin structure, architecture and lncRNA function.
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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 | 0.000 | 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 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".