Epigenomic modifications induced by hatchery rearing persist in germ line cells of adult salmon after their oceanic migration
Bibliographic record
Abstract
Abstract Human activities induce direct or indirect selection pressure on natural population and may ultimately affect population's integrity. While numerous conservation programs aimed to minimize human‐induced genomic variation, human‐induced environmental variation may generate epigenomic variation potentially affecting fitness through phenotypic modifications. Major questions remain pertaining to how much epigenomic variation arises from environmental heterogeneity, whether this variation can persist throughout life, and whether it can be transmitted across generations. We performed whole genome bisulfite sequencing (WGBS) on the sperm of genetically indistinguishable hatchery and wild‐born migrating adults of Coho salmon (Oncorhynchus kisutch) from two geographically distant rivers at different epigenome scales. Our results showed that coupling WGBS with fine‐scale analyses (local and chromosomal) allows the detection of parallel early‐life hatchery‐induced epimarks that differentiate wild from hatchery‐reared salmon. Four chromosomes and 183 differentially methylated regions (DMRs) displayed a significant signal of methylation differentiation between hatchery and wild‐born Coho salmon. Moreover, those early‐life epimarks persisted in germ line cells despite about 1.5 year spent in the ocean following release from hatchery, opening the possibility for transgenerational inheritance. Our results strengthen the hypothesis that epigenomic modifications environmentally induced during early‐life development persist in germ cells of adults until reproduction, which could potentially impact their fitness.
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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".