Hybridization between genetically modified Atlantic salmon and wild brown trout reveals novel ecological interactions
Bibliographic record
Abstract
Interspecific hybridization is a route for transgenes from genetically modified (GM) animals to invade wild populations, yet the ecological effects and potential risks that may emerge from such hybridization are unknown. Through experimental crosses, we demonstrate transmission of a growth hormone transgene via hybridization between a candidate for commercial aquaculture production, GM Atlantic salmon (Salmo salar) and closely related wild brown trout (Salmo trutta). Transgenic hybrids were viable and grew more rapidly than transgenic salmon and other non-transgenic crosses in hatchery-like conditions. In stream mesocosms designed to more closely emulate natural conditions, transgenic hybrids appeared to express competitive dominance and suppressed the growth of transgenic and non-transgenic (wild-type) salmon by 82 and 54 per cent, respectively. To the best of our knowledge, this is the first demonstration of environmental impacts of hybridization between a GM animal and a closely related species. These results provide empirical evidence of the first steps towards introgression of foreign transgenes into the genomes of new species and contribute to the growing evidence that transgenic animals have complex and context-specific interactions with wild populations. We suggest that interspecific hybridization be explicitly considered when assessing the environmental consequences should transgenic animals escape to nature.
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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 | 0.001 |
| Scholarly communication | 0.000 | 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".