Regulation of ribosomal protein genes: An ordered anarchy
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Bibliographic record
Abstract
Ribosomal protein genes are among the most highly expressed genes in most cell types. Their products are generally essential for ribosome synthesis, which is the cornerstone for cell growth and proliferation. Many cellular resources are dedicated to producing ribosomal proteins and thus this process needs to be regulated in ways that carefully balance the supply of nascent ribosomal proteins with the demand for new ribosomes. Ribosomal protein genes have classically been viewed as a uniform interconnected regulon regulated in eukaryotic cells by target of rapamycin and protein kinase A pathway in response to changes in growth conditions and/or cellular status. However, recent literature depicts a more complex picture in which the amount of ribosomal proteins produced varies between genes in response to two overlapping regulatory circuits. The first includes the classical general ribosome-producing program and the second is a gene-specific feature responsible for fine-tuning the amount of ribosomal proteins produced from each individual ribosomal gene. Unlike the general pathway that is mainly controlled at the level of transcription and translation, this specific regulation of ribosomal protein genes is largely achieved through changes in pre-mRNA splicing efficiency and mRNA stability. By combining general and specific regulation, the cell can coordinate ribosome production, while allowing functional specialization and diversity. Here we review the many ways ribosomal protein genes are regulated, with special focus on the emerging role of posttranscriptional regulatory events in fine-tuning the expression of ribosomal protein genes and its role in controlling the potential variation in ribosome functions. This article is categorized under: Translation > Ribosome Biogenesis Translation > Ribosome Structure/Function Translation > Translation Regulation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it