Genetic consequences of interbreeding between farmed and wild Atlantic salmon: insights from the transcriptome
Bibliographic record
Abstract
Large annual escapees of farmed Atlantic salmon enhance the risk of extinction of wild populations through genetic and ecological interactions. Recently, we documented evolutionary change in gene transcription between farmed and wild Atlantic salmon after only five generations of artificial selection. While differences for most quantitative traits are expected to gradually dilute through repeated backcrossing to wild populations, the genetic basis of gene transcription has been shown to be largely nonadditive and hybrid crosses may display unexpected inheritance patterns. This makes it difficult to predict to what extent interbreeding between farmed and wild individuals will change the genetic makeup of wild salmon populations. Here, we compare the genome-wide gene transcription profiles of Norwegian wild salmon to that of a second generation hybrid cross [backcross: (Farmed X Wild) X Wild]. Over 6% (298, q-value < 0.01) of the detected genes exhibited highly significantly different transcription levels, and the range and average magnitude of those differences was strikingly higher than previously described between pure farmed and wild strains. Most differences appear to result from nonadditive gene interactions. These results suggest that interbreeding of fugitive farmed salmon and wild individuals could substantially modify the genetic control of gene transcription in natural populations exposed to high migration from fish farms, resulting in potentially detrimental effects on the survival of these populations. This further supports the idea that measures to considerably reduce the number of escaped farmed salmon and their reproduction in the wild are urgently needed.
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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".