A Casz1 - NuRD complex regulates temporal identity transitions in neural progenitors
Bibliographic record
Abstract
Abstract Neural progenitor cells alter their output over developmental time to generate different types of neurons and glia in the correct sequences and proportions. A number of ‘temporal identity factors’ that control transitions in progenitor competence have been identified, but the molecular mechanisms underlying their function remain unclear. Here, we asked how the transcription factor Casz1 , the mammalian orthologue of Drosophila castor, regulates competence during retinal neurogenesis. We show that Casz1 is required to control the transition between neurogenesis and gliogenesis. Using BioID proteomics, we reveal that Casz1 interacts with the nucleosome remodeling and deacetylase (NuRD) complex in retinal cells. Finally, we show that both the NuRD and the polycomb repressor complexes are required for Casz1 to promote the rod fate and suppress gliogenesis. As other temporal identity factors have been found to interact with the NuRD complex in other contexts, we propose that these factors might act through a common biochemical process to regulate neurogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".