Distribution and dynamics of mitochondrial DNA methylation in oocytes, embryos and granulosa cells
Bibliographic record
Abstract
Comparison of mitochondrial DNA (mtDNA) methylation patterns in oocytes, blastocysts and ovarian granulosa cells indicates hitherto unsuspected dynamics. Oocytes and blastocysts recovered from cows subjected to ovarian stimulation and from non-stimulated abattoir ovaries were analyzed using bisulphite transformation of DNA followed by whole genome sequencing. The cow is a recognized as a good model for human oocyte and pre-implantation development. The number of mtDNA copies is high in oocytes (200,000-400,000) and early embryos, resulting in very high coverage (>3000x) and very low p values for each of 716 cytosine-based nucleosides. Methylation ratio was lowest in oocytes, following by blastocysts then granulosa cells and was not restricted to CG sites but was found also at CHG and CHH sites. The initial methylation pattern is conserved during the first week of life but not in somatic cells. RNA analysis of mitochondria encoded genes showed a significant inverse correlation between methylation and expression for almost all sequences. Methylation was more extensive in somatic tissues from mature animals than in immature pre-pubertal animals. Our findings suggest that mtDNA methylation might play a programming role during gametogenesis and would be subject to epigenetic regulation according to environment and/or maternal maturity.
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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".