LncRNA CISTR-ACT regulates cell size in human and mouse by guiding FOSL2
Bibliographic record
Abstract
Organisms regulate cell size and shape to function efficiently. Aberrant cell morphogenesis is commonly associated with disease, yet gene-regulatory mechanisms remain unknown. CISTR-ACT was the first lncRNA involved in inter-chromosomal proximities and Mendelian disease, and it is associated with mean corpuscular volume (red blood cell size). Here, functional dissection of CISTR-ACT’s DNA- and RNA-encoded mechanisms by in vitro and in vivo perturbations reveals that CISTR-ACT regulates cell size across cell types and species. CISTR-ACT’s locus is embedded in a stable inter-chromosomal environment which contains cell size genes that are regulated by CISTR-ACT in trans. CISTR-ACT’s RNA also has function and directly interacts with transcription factor FOSL2 to guide its regulation of cell morphogenesis and cell-cell adhesion genes. In the absence of CISTR-ACT, the FOSL2-chromatin binding is perturbed. Our study exemplifies how a functionally conserved lncRNA regulates cell size with multiple modes of action and ultimately contributes to clinically relevant phenotypes. Establishment and maintenance of appropriate cell size is a prerequisite for cells to function efficiently. Here, Kiriakopulos et al. reveal that the lncRNA CISTR-ACT maintains cell size across cell types in humans and mice by regulating cell morphogenesis genes in trans via guidance of the transcription factor FOSL2.
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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 | 0.000 |
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".