Role of the Ubiquitin Ligase RNF149 in the Development of Rat Neonatal Gonocytes
Bibliographic record
Abstract
Male reproductive function depends on the formation of spermatogonial stem cells from their neonatal precursors, the gonocytes. Previously, we identified several UPS enzymes dynamically altered during gonocyte differentiation. The present work focuses on understanding the role of the RING finger protein 149 (RNF149), an E3 ligase that we found to be strongly expressed in gonocytes and downregulated in spermatogonia. The quantification of RNF149 mRNA from postnatal day (PND) 2 to 35 (puberty) in rat testis, brain, liver, kidney, and heart indicated that its highest levels are found in the testis. RNF149 knock-down in PND3 rat gonocytes was performed to better understand its role in gonocyte development. While a proliferative cocktail of PDGF-BB and 17β-estradiol (P+E) increased both the expression levels of the cell proliferation marker PCNA and RNF149 in mock cells, the effects of P+E on both genes were reduced in cells treated with RNF149 siRNA, suggesting that RNF149 expression is regulated during gonocyte proliferation and that there might be a functional link between RNF149 and PCNA. To examine RNF149 subcellular localization, EGFP-tagged RNF149 vectors were constructed, after determining the rat testis RNF149 mRNA sequence. Surprisingly, two variant transcripts were expressed in rat tissues, predicting truncated proteins, one containing the PA and the other the RING functional domains. Transfection in mouse F9 embryonal carcinoma cells and C18-4 spermatogonial cell lines showed differential subcellular profiles of the two truncated proteins. Overall, the results of this study support a role for RNF149 in gonocyte proliferation and suggest its transcription to variant mRNAs resulting in two proteins with different functional domains. Future studies will examine the respective roles of these variant proteins in the cell lines and isolated gonocytes.
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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".