Genome-wide characterisation of Foxa1 binding sites reveals several mechanisms for regulating neuronal differentiation in midbrain dopamine cells
Bibliographic record
Abstract
Midbrain dopamine neuronal progenitors develop into heterogeneous subgroups of neurons, such as substantia nigra pars compacta, ventral tegmental area and retrorubal field, that regulate motor control, motivated and addictive behaviours. The development of midbrain dopamine neurons has been extensively studied, and these studies indicate that complex cross-regulatory interactions between extrinsic and intrinsic molecules regulate a precise temporal and spatial programme of neurogenesis in midbrain dopamine progenitors. To elucidate direct molecular interactions between multiple regulatory factors during neuronal differentiation in mice, we characterised genome-wide binding sites of the forkhead/winged helix transcription factor Foxa1, which functions redundantly with Foxa2 to regulate the differentiation of mDA neurons. Interestingly, our studies identified a rostral brain floor plate Neurog2 enhancer that requires direct input from Otx2, Foxa1, Foxa2 and an E-box transcription factor for its transcriptional activity. Furthermore, the chromatin remodelling factor Smarca1 was shown to function downstream of Foxa1 and Foxa2 to regulate differentiation from immature to mature midbrain dopaminergic neurons. Our genome-wide Foxa1-bound cis-regulatory sequences from ChIP-Seq and Foxa1/2 candidate target genes from RNA-Seq analyses of embryonic midbrain dopamine cells also provide an excellent resource for probing mechanistic insights into gene regulatory networks involved in the differentiation of midbrain dopamine neurons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".