Constitutive activation of CTNNB1 results in a loss of spermatogonial stem cell activity in mice
Bibliographic record
Abstract
Spermatogenesis requires that a careful balance be maintained between the self-renewal of spermatogonial stem cells (SSCs) and their commitment to the developmental pathway through which they will differentiate into spermatozoa. Recently, a series of studies employing various in vivo and in vitro models have suggested a role of the wingless-related MMTV integration site gene family/beta-catenin (WNT/CTNNB1) pathway in determining the fate of SSCs. However, conflicting data have suggested that CTNNB1 signaling may either promote SSC self-renewal or differentiation. Here, we studied the effects of sustained CTNNB1 signaling in SSCs using the Ctnnb1tm1Mmt/+; Ddx4-CreTr/+ (ΔCtnnb1) mouse model, in which a stabilized form of CTNNB1 is expressed in all germ cells. ΔCtnnb1 mice were found to have reduced testis weights and partial germ cell loss by 4 months of age. Germ cell transplantation assays showed a 49% reduction in total functional SSC numbers in 8 month-old transgenic mice. In vitro, Thy1-positive undifferentiated spermatogonia from ΔCtnnb1 mice formed 57% fewer clusters, which was associated with decreased cell proliferation. A reduction in mRNA levels of genes associated with SSC maintenance (Bcl6b, Gfra1, Plzf) and increased levels for markers associated with progenitor and differentiating spermatogonia (Kit, Rarg, Sohlh1) were detected in these cluster cells. Furthermore, RNAseq performed on these clusters revealed a network of more than 900 genes regulated by CTNNB1, indicating that CTNNB1 is an important regulator of spermatogonial fate. Together, our data support the notion that CTNNB1 signaling promotes the transition of SSCs to undifferentiated progenitor spermatogonia at the expense of their self-renewal.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".