Proteasome regulation of the chromodomain protein MRG-1 controls the balance between proliferative fate and differentiation in the<i>C. elegans</i>germ line
Bibliographic record
Abstract
The level of stem cell proliferation must be tightly controlled for proper development and tissue homeostasis. Multiple levels of gene regulation are often employed to regulate stem cell proliferation to ensure that the amount of proliferation is aligned with the needs of the tissue. Here we focus on proteasome-mediated protein degradation as a means of regulating the activities of proteins involved in controlling the stem cell proliferative fate in the C. elegans germ line. We identify five potential E3 ubiquitin ligases, including the RFP-1 RING finger protein, as being involved in regulating proliferative fate. RFP-1 binds to MRG-1, a homologue of the mammalian chromodomain-containing protein MRG15 (MORF4L1), which has been implicated in promoting the proliferation of neural precursor cells. We find that C. elegans with reduced proteasome activity, or that lack RFP-1 expression, have increased levels of MRG-1 and a shift towards increased proliferation in sensitized genetic backgrounds. Likewise, reduction of MRG-1 partially suppresses stem cell overproliferation. MRG-1 levels are controlled independently of the spatially regulated GLP-1/Notch signalling pathway, which is the primary signal controlling the extent of stem cell proliferation in the C. elegans germ line. We propose a model in which MRG-1 levels are controlled, at least in part, by the proteasome, and that the levels of MRG-1 set a threshold upon which other spatially regulated factors act in order to control the balance between the proliferative fate and differentiation in the C. elegans germ line.
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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 | 0.000 |
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".