Differential usage of two, distinct DNA-binding domains regulates tissue-specific occupancy of the pioneer factor Zelda
Bibliographic record
Abstract
Abstract Pioneer transcription factors act at the top of gene-regulatory networks by promoting accessible chromatin at the cis -regulatory regions that drive gene expression. Despite their ability to bind closed chromatin, pioneer factors occupy distinct binding sites in different tissues. The pioneer factor Zelda promotes the undifferentiated fate in both the early Drosophila embryo and in the neural stem cells (neuroblasts) of the larval brain. Tissue-specific binding by Zelda identifies cell-type specific enhancers, which are enriched for different DNA-sequence motifs. We investigated the features that promoted cell-type specific occupancy by testing the role of conserved, structured protein domains in the capacity of Zelda to promote the embryonic and neuroblast cell fates. We unexpectedly identified that the most deeply conserved region in Zelda, the second zinc finger, has opposing functions in the embryo and neuroblasts. We showed that this zinc finger is a previously unrecognized DNA-binding domain that is specifically required for Zelda binding to a G-rich motif in larval neuroblasts. The pioneering function of Zelda depends largely on the C-terminal cluster of zinc fingers that promotes binding in the early embryo, suggesting that pioneer function may depend on how Zelda engages the genome. As opposed to co-factor expression or chromatin environment, our data identify tissue-specific usage of two, widely separated DNA-binding domains as the mechanism controlling tissue-specific binding and activity.
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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".