Third-Generation Sequencing Reveals the Adaptive Role of the Epigenome in Three Deep-Sea Polychaetes
Bibliographic record
Abstract
The roles of DNA methylation in invertebrates are poorly characterized, and critical data are missing for the phylum Annelida. We fill this knowledge gap by conducting the first genome-wide survey of DNA methylation in the deep-sea polychaetes dominant in deep-sea vents and seeps: Paraescarpia echinospica, Ridgeia piscesae, and Paralvinella palmiformis. DNA methylation calls were inferred from Oxford Nanopore sequencing after assembling high-quality genomes of these animals. The genomes of these worms encode all the key enzymes of the DNA methylation metabolism and possess a mosaic methylome similar to that of other invertebrates. Transcriptomic data of these polychaetes support the hypotheses that gene body methylation strengthens the expression of housekeeping genes and that promoter methylation acts as a silencing mechanism but not the hypothesis that DNA methylation suppresses the activity of transposable elements. The conserved epigenetic profiles of genes responsible for maintaining homeostasis under extreme hydrostatic pressure suggest DNA methylation plays an important adaptive role in these worms.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".