Strong Parallel Differential Gene Expression Induced by Hatchery Rearing Weakly Associated with Methylation Signals in Adult Coho Salmon (<i>O. kisutch</i>)
Bibliographic record
Abstract
Human activities and resource exploitation led to a massive decline of wild salmonid populations, consequently, numerous conservation programs have been developed to supplement wild populations. However, many studies documented reduced fitness of hatchery-born relative to wild fish. Here, by using both RNA sequencing and Whole Genome Bisulfite Sequencing of hatchery and wild-born adult Coho salmon (Oncorhynchus kisutch) originating from two previously studied river systems, we show that early-life hatchery-rearing environment-induced significant and parallel gene expression differentiation is maintained until Coho come back to their natal river for reproduction. A total of 3,643 genes differentially expressed and 859 coexpressed genes were downregulated in parallel in hatchery-born fish from both rivers relative to their wild congeners. Among those genes, 26 displayed a significant relationship between gene expression and the median gene body methylation and 669 single CpGs displayed a significant correlation between methylation level and the associated gene expression. The link between methylation and gene expression was weak suggesting that DNA methylation is not the only player in mediating hatchery-related expression differences. Yet, significant gene expression differentiation was observed despite 18 months spent in a common environment (i.e., the sea). Finally, the differentiation is observed in parallel in two different river systems, highlighting the fact that early-life environment may account for at least some of the reduced fitness of the hatchery salmon in the wild. These results illustrate the relevance and importance of considering both epigenome and transcriptome to evaluate the costs and benefits of large-scale supplementation programs.
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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".