Identification of Integrin-α4, Rb1, and Syncytin A as Murine Placental Target Genes of the Transcription Factor GCMa/Gcm1
Bibliographic record
Abstract
Members of the GCM (glial cells missing) transcription factor family have been shown to act as master regulators in different cells during mammalian and fly development being responsible for processes including gliogenesis, hematopoiesis, placental formation, and development of the parathyroidea. In the central nervous system of flies, several target genes for GCM have been reported, namely repo, pointed, and tramtrack. In mammals, two GCM genes are known (GCMa and GCMb), but the knowledge of their target genes is very limited. Here, we present for the first time a global approach aimed to identify GCMa target genes. We found 66 genes up-regulated and 11 genes down-regulated in GCMa-deficient chorionic tissue of mice at embryonic day 9.5. Moreover, we verified by quantitative reverse transcription-PCR all 11 down-regulated genes. The two most strongly down-regulated genes, integrin-alpha4 and retinoblastoma (Rb1), were further analyzed by promoter studies. Additionally, we identified down-regulation of the murine syncytin A gene, which is fundamental for syncytiotrophoblast formation. Finally, we proved strong down-regulation of integrin-alpha4 and Rb1 transcript levels by in situ hybridization in murine GCMa-deficient placentae at embryonic day 9.5. Our data demonstrate for the first time that genes encoding key regulators of placental tissue formation and architecture are regulated by GCMa.
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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".