Identification of a direct Dlx homeodomain target in the developing mouse forebrain and retina by optimization of chromatin immunoprecipitation
Bibliographic record
Abstract
Understanding homeobox gene specificity and function has been hampered by the lack of proven direct transcriptional targets during development. Dlx genes are expressed in the developing forebrain, retina, craniofacial structures and limbs. Dlx1/Dlx2 double knockout mice die at birth with multiple defects including abnormal forebrain development and decreased Dlx5 and Dlx6 expression. We have successfully applied chromatin immunoprecipitation (ChIP) to identify a direct transcriptional target of DLX homeoproteins from embryonic tissues in vivo. We optimized cross-linking conditions to enrich for protein-DNA complexes, then using specific high affinity DLX antibodies captured immunoenriched DLX genomic DNA transcriptional targets. DLX homeobox proteins bind differentially to the Dlx5/Dlx6 intergenic enhancer in newborn retina (DLX2) and embryonic striatum (DLX1, DLX2) in situ. Reporter gene assays demonstrated the functional significance of the binding of DLX proteins to this regulatory element, confirmed in vitro by electrophoretic mobility shift assays, using tissue extracts or recombinant DLX proteins. ChIP provides the best approach to identify direct Dlx homeoprotein targets from developing tissues in situ. The use of this technology will advance our understanding of Dlx gene function in the vertebrate in vivo and can be applied to examine targets of other homeobox genes and other classes of transcription factors.
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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 | 0.001 |
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".