An <i>Nlrp5</i> -null mutation leads to attenuated <i>de novo</i> methylation in oocytes, accompanied by a significant reduction in DNMT3L
Bibliographic record
Abstract
Abstract Nlrp5 encodes a core component of the subcortical maternal complex (SCMC) a cytoplasmic protein structure unique to the mammalian oocyte and cleavage-stage embryo. NLRP5 mutations have been identified in patients presenting with early embryo arrest, recurrent molar pregnancies and imprinting disorders. Correct patterning of DNA methylation over imprinted domains during oogenesis is necessary for faithful imprinting of genes. It was previously shown that oocytes with mutation in the human SCMC gene KHDC3L had globally impaired methylation, indicating that integrity of the SCMC is essential for correct establishment of DNA methylation at imprinted regions. Here, we present a multi-omic analysis of an Nlrp5 - null mouse model, which in GV oocytes displays a misregulation of a broad range of maternal proteins, including proteins involved in several key developmental processes. This misregulation likely underlies impaired oocyte developmental competence. Amongst impacted proteins are several epigenetic modifiers, including a substantial reduction in DNMT3L; we show that de novo DNA methylation is attenuated in Nlrp5 -null oocytes. This provides evidence for mechanisms leading to downstream misregulation of imprinted genes, which in turn, may result in imprinting syndromes, multi-locus imprinting disturbances (MLID) and hydatidiform moles.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".