A transcriptome analysis of mouse pituitary development: implication of Etv1 and Pax7 transcription factors in POMC transcription and cell differentiation
Bibliographic record
Abstract
As the key organ in the endocrine system, the pituitary has long been the subject of intense scientific questioning. From the characterization of pituitary hormones to the understanding of the mechanisms controlling their release, the study of the pituitary yielded great discoveries, some being awarded a Nobel prize. More recently, the transcriptional control of genes encoding pituitary hormones was the object of much attention. In that context, our laboratory described the function of Tpit and NeuroD1 in the control of POMC-expressing cell differentiation and POMC cell-specific transcription and regulatory mechanisms. These two important genes do not suffice however to explain every aspect of POMC cell differentiation. We thus undertook the systematic screening of the developing and adult pituitary transcriptome in a search for novel transcriptional regulators. Using state of the art bioinformatic tools, we observed the concerted variations of biologically relevant gene groups as the organ develops and matures. Using a candidate gene approach, we identified new transcription factors expressed in POMC lineages. We describe for the first time the expression of Etv1, an Ets-domain containing factor, in the pituitary. We showed that Etv1 expression is specific to POMC cells and that it is important for activation of Pomc transcription in collaboration with Tpit and Pitx1. Furthermore, we demonstrated the melanotroph-specific expression of Pax7 in the pituitary, establishing a clear distinction between the two Pomc-expressing lineages at the transcriptional level. Using Pax7 knock-out mice, we determined the impact of this transcription factor on the genetic program of Pomc cells. Pax7 plays a major role in activating melanotroph genes and repressing corticotroph genes. In summary, our bio-informatic analysis yielded extremely relevant data with regard to pituitary development, particularly through the elucidation of key critical roles for Etv1 and Pax7 in Pomc cell biology.
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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 | 0.000 |
| 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".