Nuclear actin-dependent <i>Meg3</i> expression suppresses metabolic genes by affecting the chromatin architecture at sites of elevated H3K27 acetylation levels
Bibliographic record
Abstract
Nuclear actin mediates enhancer-dependent transcriptional regulation at compartment level, playing critical roles in 3D genome organization. In β-actin depleted cells, H3K27 acetylation is enhanced, directly affecting enhancer-dependent transcriptional regulation and gene expression changes during compartment-switching. Here, we report these mechanisms are influenced by the long non-coding RNA (lncRNA) Meg3. Bulk RNA-seq analysis and qPCR on wild-type (WT), heterozygous (HET), and β-actin knockout (KO) mouse embryonic fibroblasts (MEFs) show that β-actin depletion significantly alters expression of several lncRNAs, including Meg3. Results from ChIRP-seq, ChIRP-MS, and fRIP-qPCR revealed that in β-actin KO cells, Meg3 becomes enriched and binds to H3K27 acetylation marks within gene regulatory regions. By integrating RNA-seq, H3K27 acetylation ChIP-seq, ATAC-seq, and HiC-seq data through activity by contact (ABC) analysis, we discovered Meg3 binding disrupts promoter-enhancer interactions in β-actin KO cells. These results, combined with metabolomics in WT, HET, and β-actin KO MEFs, show Meg3 binding to regulatory regions at sites of increased H3K27 acetylation impairs the expression of genes involved in the synthesis of chondroitin, heparan, dermatan sulfate, and phospholipases. We propose that in β-actin KO cells Meg3 binds to H3K27 acetylation levels. This interferes with promoter-enhancer interactions, disrupts genome organization, and downregulates gene expression and key metabolic pathways.
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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) | 0.002 | 0.001 |
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".