It Takes a Village of Chromatin Remodelers to Regulate rDNA Expression
Bibliographic record
Abstract
Ribosome biogenesis is one of the most fundamental and energetically demanding cellular processes. In humans, the ribosomal DNA (rDNA) repeats span a large region of DNA and comprise 200 to 600 copies of a ~43 kb unit spread over five different chromosomes. Control over ribosome biogenesis is closely tied to the regulation of the chromatin environment of this large genomic region. The proportion of rDNA loci which are active or silent is altered depending on the proliferative or metabolic state of the cell. Repeat silencing is driven by epigenetic changes culminating in a repressive heterochromatin environment. One group of proteins facilitating these epigenetic changes in response to growth or metabolic demands are ATP-dependent chromatin remodeling protein complexes that use ATP hydrolysis to reposition nucleosomes. Indeed, some chromatin remodelers are known to have indispensable roles in regulating the chromatin environment of rDNA. In this review, we highlight these proteins and their complexes and describe their mechanistic roles at rDNA. We also introduce the developmental disorders arising from the dysfunction of these proteins and discuss how the consequent dysregulation of rDNA loci may be reflected in the phenotypes observed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".