The Transcriptional Regulator SnoN Promotes the Proliferation of Cerebellar Granule Neuron Precursors in the Postnatal Mouse Brain
Bibliographic record
Abstract
Control of neuronal precursor cell proliferation is essential for normal brain development, and deregulation of this fundamental developmental event contributes to brain diseases. Typically, neuronal precursor cell proliferation extends over long periods of time during brain development. However, how neuronal precursor proliferation is regulated in a temporally specific manner remains to be elucidated. Here, we report that conditional KO of the transcriptional regulator SnoN in cerebellar granule neuron precursors robustly inhibits the proliferation of these cells and promotes their cell cycle exit at later stages of cerebellar development in the postnatal male and female mouse brain. In laser capture microdissection followed by RNA-Seq, designed to profile gene expression specifically in the external granule layer of the cerebellum, we find that SnoN promotes the expression of cell proliferation genes and concomitantly represses differentiation genes in granule neuron precursorsin vivo. Remarkably, bioinformatics analyses reveal that SnoN-regulated genes contain binding sites for the transcription factors N-myc and Pax6, which promote the proliferation and differentiation of granule neuron precursors, respectively. Accordingly, we uncover novel physical interactions of SnoN with N-myc and Pax6 in cells. In behavior analyses, conditional KO of SnoN impairs cerebellar-dependent learning in a delayed eye-blink conditioning paradigm, suggesting that SnoN-regulation of granule neuron precursor proliferation bears functional consequences at the organismal level. Our findings define a novel function and mechanism for the major transcriptional regulator SnoN in the control of granule neuron precursor proliferation in the mammalian brain. SIGNIFICANCE STATEMENTThis study reports the discovery that the transcriptional regulator SnoN plays a crucial role in the proliferation of cerebellar granule neuron precursors in the postnatal mouse brain. Conditional KO of SnoN in granule neuron precursors robustly inhibits the proliferation of these cells and promotes their cycle exit specifically at later stages of cerebellar development, with biological consequences of impaired cerebellar-dependent learning. Genomics and bioinformatics analyses reveal that SnoN promotes the expression of cell proliferation genes and concomitantly represses cell differentiation genesin vivo. Although SnoN has been implicated in distinct aspects of the development of postmitotic neurons, this study identifies a novel function for SnoN in neuronal precursors in the mammalian brain.
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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".