RSL24D1 sustains steady-state ribosome biogenesis and pluripotency translational programs in embryonic stem cells
Bibliographic record
Abstract
Abstract Embryonic stem cell (ESC) fate decisions are regulated by a complex molecular circuitry that requires tight and coordinated gene expression regulations at multiple levels from chromatin organization to mRNA processing. Recently, ribosome biogenesis and translation have emerged as key regulatory pathways that efficiently control stem cell homeostasis. However, the molecular mechanisms underlying the regulation of these pathways remain largely unknown to date. Here, we analyzed the expression, in mouse ESCs, of over 300 genes involved in ribosome biogenesis and we identified RSL24D1 as the most differentially expressed between self-renewing and differentiated ESCs. RSL24D1 is highly expressed in multiple mouse pluripotent stem cell models and its expression profile is conserved in human ESCs. RSL24D1 is associated with nuclear pre-ribosomes and is required for the maturation and the synthesis of 60S subunits in mouse ESCs. Interestingly, RSL24D1 depletion significantly impairs global translation, particularly of key pluripotency factors, including POU5F1 and NANOG, as well as components of the polycomb repressive complex 2 (PRC2). Consistently, RSL24D1 is required for mouse ESC self-renewal and proliferation. Taken together, we show that RSL24D1-dependant ribosome biogenesis is required to both sustain the expression of pluripotent transcriptional programs and silence developmental programs, which concertedly dictate ESC homeostasis.
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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 | 0.001 |
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".