Neurog2 Simultaneously Activates and Represses Alternative Gene Expression Programs in the Developing Neocortex
Bibliographic record
Abstract
Progenitor cells undergo a series of stable identity transitions on their way to becoming fully differentiated cells with unique identities. Each cellular transition requires that new sets of genes are expressed, while alternative genetic programs are concurrently repressed. Here, we investigated how the proneural gene Neurog2 simultaneously activates and represses alternative gene expression programs in the developing neocortex. By comparing the activities of transcriptional activator (Neurog2-VP16) and repressor (Neurog2-EnR) fusions to wild-type Neurog2, we first demonstrate that Neurog2 functions as an activator to both extinguish Pax6 expression in radial glial cells and initiate Tbr2 expression in intermediate neuronal progenitors. Similarly, we show that Neurog2 functions as an activator to promote the differentiation of neurons with a dorsal telencephalic (i.e., neocortical) identity and to block a ventral fate, identifying 2 Neurog2-regulated transcriptional programs involved in the latter. First, we show that the Neurog2-transcriptional target Tbr2 is a direct transcriptional repressor of the ventral gene Ebf1. Secondly, we demonstrate that Neurog2 indirectly turns off Etv1 expression, which in turn indirectly regulates the expression of the ventral proneural gene Ascl1. Neurog2 thus activates several genetic off-switches, each with distinct transcriptional targets, revealing an unappreciated level of specificity for how Neurog2 prevents inappropriate gene expression during neocortical development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".