Ikaros family proteins redundantly regulate temporal patterning in the developing mouse retina
Bibliographic record
Abstract
Temporal identity factors regulate competence of neural progenitors to generate specific cell types in a time-dependent manner, but how they operate remains poorly defined. In the developing mouse retina, the Ikaros zinc-finger transcription factor Ikzf1 regulates production of early-born cell types, except cone photoreceptors. In this study we show that, during early stages of retinal development, another Ikaros family protein, Ikzf4, functions redundantly with Ikzf1 to regulate cone photoreceptor production. Using CUT&RUN and functional assays, we show that Ikzf4 binds and represses genes involved in late-born rod photoreceptor specification, hence favoring cone production. At late stages, when Ikzf1 is no longer expressed in progenitors, we show that Ikzf4 re-localizes to target genes involved in gliogenesis and is required for Müller glia production. We report that Ikzf4 regulates Notch signaling genes and is sufficient to activate the Hes1 promoter through two Ikzf GGAA-binding motifs, suggesting a mechanism by which Ikzf4 may influence gliogenesis. These results uncover a combinatorial role for Ikaros family members during nervous system development and provide mechanistic insights on how they temporally regulate cell fate output.
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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 | 0.001 | 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 | 0.001 |
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".