Mitochondrial epigenetics brings new perspectives on doubly uniparental inheritance in bivalves
Bibliographic record
Abstract
Mitochondrial epigenetics, particularly mtDNA methylation, is a flourishing field of research. MtDNA methylation appears to play multiple roles, including regulating mitochondrial transcription, cell metabolism and mitochondrial inheritance. In animals, bivalves with doubly uniparental inheritance (DUI) of mitochondria are the exception to the rule of maternal mitochondrial inheritance since DUI also involve a paternal mtDNA transmitted from the father to sons. The mechanisms underlying DUI are still unknown, but mtDNA methylation could play a role in its regulation. Here, we investigated mtDNA methylation levels and machinery in gonads of the mussel Mytilus edulis using methods based on antibodies, enzymatic cleavage and methylome sequencing. Our results confirm the presence in mitochondria of methylated cytosines and adenines and methyltransferases and unveil a more variable cytosine methylation state among males than females. Also, spermatid mtDNA is always methylated, while only few spermatozoa present methylated mtDNA suggesting a relation between cytosine methylation and development stage of male gametes. We propose that mtDNA methylation could play a role in the different fates of the parental mtDNAs in male and female embryos in M. edulis. Our study provides novel insights into the epigenetic landscape of bivalve mtDNA and highlights the multiple roles of mtDNA methylation in animals.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".