Divergent functions of the proneural genes <i>Mash1</i> and <i>Ngn2</i> in the specification of neuronal subtype identity
Bibliographic record
Abstract
The neural bHLH genes Mash1 and Ngn2 are expressed in complementary populations of neural progenitors in the central and peripheral nervous systems. Here, we have systematically compared the activities of the two genes during neural development by generating replacement mutations in mice in which the coding sequences of Mash1 and Ngn2 were swapped. Using this approach, we demonstrate that Mash1 has the capacity to respecify the identity of neuronal populations normally derived from Ngn2-expressing progenitors in the dorsal telencephalon and ventral spinal cord. In contrast, misexpression of Ngn2 in Mash1-expressing progenitors does not result in any overt change in neuronal phenotype. Taken together, these results demonstrate that Mash1 and Ngn2 have divergent functions in specification of neuronal subtype identity, with Mash1 having the characteristics of an instructive determinant whereas Ngn2 functions as a permissive factor that must act in combination with other factors to specify neuronal phenotypes. Moreover, the ectopic expression of Ngn2 can rescue the neurogenesis defects of Mash1 null mutants in the ventral telencephalon and sympathetic ganglia but not in the ventral spinal cord and the locus coeruleus, indicating that Mash1 contribution to the specification of neuronal fates varies greatly in different lineages, presumably depending on the presence of other determinants of neuronal identity.
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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".