The LGN protein promotes planar proliferative divisions in the neocortex but apicobasal asymmetric terminal divisions in the retina
Bibliographic record
Abstract
Cell division orientation is crucial to control segregation of polarized fate determinants in the daughter cells to produce symmetric or asymmetric fate outcomes. Most studies in vertebrates have focused on the role of mitotic spindle orientation in proliferative asymmetric divisions and it remains unclear whether altering spindle orientation is required for the production of asymmetric fates in differentiative terminal divisions. Here, we show that the GoLoco motif protein LGN, which interacts with Gαi to control apicobasal division orientation in Drosophila neuroblasts, is excluded from the apical domain of retinal progenitors undergoing planar divisions, but not in those undergoing apicobasal divisions. Inactivation of LGN reduces the number of apicobasal divisions in mouse retinal progenitors, whereas it conversely increases these divisions in cortical progenitors. Although LGN inactivation increases the number of progenitors outside the ventricular zone in the developing neocortex, it has no effect on the position or number of progenitors in the retina. Retinal progenitor cell lineage analysis in LGN mutant mice, however, shows an increase in symmetric terminal divisions producing two photoreceptors, at the expense of asymmetric terminal divisions producing a photoreceptor and a bipolar or amacrine cell. Similarly, inactivating Gαi decreases asymmetric terminal divisions, suggesting that LGN function with Gαi to control division orientation in retinal progenitors. Together, these results show a context-dependent function for LGN and indicate that apicobasal divisions are not involved in proliferative asymmetric divisions in the mouse retina, but are instead essential to generate binary fates at terminal divisions.
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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".