The Dlx5 and Foxg1 transcription factors, linked via miRNA-9 and -200, are required for the development of the olfactory and GnRH system
Bibliographic record
Abstract
During neuronal development and maturation, microRNAs (miRs) play diverse functions ranging from early patterning, proliferation and commitment to differentiation, survival, homeostasis, activity and plasticity of more mature and adult neurons. The role of miRs in the differentiation of olfactory receptor neurons (ORNs) is emerging from the conditional inactivation of Dicer in immature ORN, and the depletion of all mature miRs in this system. Here, we identify specific miRs involved in olfactory development, by focusing on mice null for Dlx5, a homeogene essential for both ORN differentiation and axon guidance and connectivity. Analysis of miR expression in Dlx5(-/-) olfactory epithelium pointed to reduced levels of miR-9, miR-376a and four miRs of the -200 class in the absence of Dlx5. To functionally examine the role of these miRs, we depleted miR-9 and miR-200 class in reporter zebrafish embryos and observed delayed ORN differentiation, altered axonal trajectory/targeting, and altered genesis and position of olfactory-associated GnRH neurons, i.e. a phenotype known as Kallmann syndrome in humans. miR-9 and miR-200-class negatively control Foxg1 mRNA, a fork-head transcription factor essential for development of the olfactory epithelium and of the forebrain, known to maintain progenitors in a stem state. Increased levels of z-foxg1 mRNA resulted in delayed ORN differentiation and altered axon trajectory, in zebrafish embryos. This work describes for the first time the role of specific miR (-9 and -200) in olfactory/GnRH development, and uncovers a Dlx5-Foxg1 regulation whose alteration affects receptor neuron differentiation, axonal targeting, GnRH neuron development, the hallmarks of the Kallmann syndrome.
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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".