Identification of Novel Gata3 Distal Enhancers Active in Mouse Embryonic Lens
Bibliographic record
Abstract
BACKGROUND: The tissue-specific transcriptional programs during normal development require tight control by distal cis-regulatory elements, such as enhancers, with specific DNA sequences recognized by transcription factors, coactivators, and chromatin remodeling enzymes. Gata3 is a sequence-specific DNA-binding transcription factor that regulates formation of multiple tissues and organs, including inner ear, lens, mammary gland, T-cells, urogenital system, and thyroid gland. In the eye, Gata3 has a highly restricted expression domain in the posterior part of the lens vesicle; however, the underlying regulatory mechanisms are unknown. RESULTS: Here we describe the identification of a novel bipartite Gata3 lens-specific enhancer located ∼18 kb upstream from its transcriptional start site. We also found that a 5-kb Gata3 promoter possesses low activity in the lens. The bipartite enhancer contains arrays of AP-1, Ets-, and Smad1/5-binding sites as well as binding sites for lens-associated DNA-binding factors. Transient transfection studies of the promoter with the bipartite enhancer showed enhanced activation by BMP4 and FGF2. CONCLUSIONS: These studies identify a novel distal enhancer of Gata3 with high activity in lens and indicate that BMP and FGF signaling can up-regulate expression of Gata3 in differentiating lens fiber cells through the identified Gata3 enhancer and promoter elements. Developmental Dynamics 247:1186-1198, 2018. © 2018 The Authors. Developmental Dynamics published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".