The CCR4-NOT Complex Mediates Deadenylation and Degradation of Stem Cell mRNAs and Promotes Planarian Stem Cell Differentiation
Bibliographic record
Abstract
Post-transcriptional regulatory mechanisms are of fundamental importance to form robust genetic networks, but their roles in stem cell pluripotency remain poorly understood. Here, we use freshwater planarians as a model system to investigate this and uncover a role for CCR4-NOT mediated deadenylation of mRNAs in stem cell differentiation. Planarian adult stem cells, the so-called neoblasts, drive the almost unlimited regenerative capabilities of planarians and allow their ongoing homeostatic tissue turnover. While many genes have been demonstrated to be required for these processes, currently almost no mechanistic insight is available into their regulation. We show that knockdown of planarian Not1, the CCR4-NOT deadenylating complex scaffolding subunit, abrogates regeneration and normal homeostasis. This abrogation is primarily due to severe impairment of their differentiation potential. We describe a stem cell specific increase in the mRNA levels of key neoblast genes after Smed-not1 knock down, consistent with a role of the CCR4-NOT complex in degradation of neoblast mRNAs upon the onset of differentiation. We also observe a stem cell specific increase in the frequency of longer poly(A) tails in these same mRNAs, showing that stem cells after Smed-not1 knock down fail to differentiate as they accumulate populations of transcripts with longer poly(A) tails. As other transcripts are unaffected our data hint at a targeted regulation of these key stem cell mRNAs by post-transcriptional regulators such as RNA-binding proteins or microRNAs. Together, our results show that the CCR4-NOT complex is crucial for stem cell differentiation and controls stem cell-specific degradation of mRNAs, thus providing clear mechanistic insight into this aspect of neoblast biology.
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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".