MicroRNA-574 suppresses oocyte maturation via targeting hyaluronan synthase 2 in porcine cumulus cells
Bibliographic record
Abstract
MicroRNAs (miRNAs) have been established as important regulators of gene expression in the mammalian ovary. A previous screen of small RNA in the porcine ovary identified the downregulation of miR-574 during oocyte maturation, although its role during this process was not established. Here, we found that miR-574 directly targets the transcript for hyaluronan synthase 2 protein (HAS2), a key enzyme in the production of extracellular matrix by the surrounding cumulus cells. Inhibiting this miRNA during in vitro maturation (IVM) increased HAS2 levels along with several markers of oocyte quality. Furthermore, inhibiting miR-574 increased oocyte meiotic progression. We then stably overexpressed miR-574 using a lentiviral vector to transduce cumulus cells during IVM. This gain-of-function approach resulted in a 50% decrease in HAS2 expression and nearly 20% reduction in oocyte progression through meiosis. To confirm the specific targeting of HAS2 by miR-574, we constructed several luciferase vectors harboring the HAS2 3'-untranslated region. Cotransfection of the reporter and miR-574 attenuated luciferase activity. After mutating the putative miR-574 binding site, however, this effect was abolished and luciferase activity remained high. Our results show that the direct targeting of HAS2 by miR-574 negatively impacts oocyte quality during IVM and that inhibiting miR-574 derepresses HAS2 expression and subsequently improves oocyte maturation. Taken together, we help to elucidate a mechanism of posttranscriptional regulation by miRNA in the mammalian ovary.
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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".