Compromised fertility disrupts Peg1 but not Snrpn and Peg3 imprinted methylation acquisition in mouse oocytes
Bibliographic record
Abstract
Growth and maturation of healthy oocytes within follicles requires bidirectional signaling and intercellular gap junctional communication. Aberrant endocrine signaling and loss of gap junctional communication between the oocyte and granulosa cells leads to compromised folliculogenesis, oocyte maturation, and oocyte competency, consequently impairing fertility. Given that oocyte-specific DNA methylation establishment at imprinted genes occurs during this growth phase, we determined whether compromised endocrine signaling and gap junctional communication would disrupt de novo methylation acquisition using ERβ and connexin37 genetic models. To compare mutant oocytes to control oocytes, DNA methylation acquisition was first examined in individual, 20-80 μm control oocytes at three imprinted genes, Snrpn, Peg3, and Peg1. We observed that each gene has its own size-dependent acquisition kinetics, similar to previous studies. To determine whether compromised endocrine signaling and gap junctional communication disrupted de novo methylation acquisition,individual oocytes from Esr2- and Gja4-deficient mice were also assessed for DNA methylation establishment. We observed no aberrant or delayed acquisition of DNA methylation at Snrpn, Peg3, or Peg1 in oocytes from Esr2-deficient females, and no perturbation in Snrpn or Peg3de novo methylation in oocytes from Gja4-null females. However, Gja4 deficiency resulted in a loss or delay in methylation acquisition at Peg1. One explanation for this difference between the three loci analyzed is the late establishment of DNA methylation at the Peg1 gene. These results indicate that compromised fertility though impaired intercellular communication can lead to imprinting acquisition errors. Further studies are required to determine the effects of subfertility/infertility originating from impaired signaling and intercellular communication during oogenesis on imprint maintenance during preimplantation development.
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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 | 0.001 |
| 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".