Population‐specific gene expression responses to hybridization between farm and wild Atlantic salmon
Bibliographic record
Abstract
Because of intrinsic differences in their genetic architectures, wild populations invaded by domesticated individuals could experience population-specific consequences following introgression by genetic material of domesticated origin. Expression levels of 16 000 transcripts were quantified by microarrays in liver tissue from farm, wild, and farm-wild backcross (i.e. F1 farm-wild hybrid × wild; total n = 50) Atlantic salmon (Salmo salar) raised under common environmental conditions. The wild populations and farm strain originated from three North American rivers in eastern Canada (Stewiacke, Tusket, and Saint John rivers, respectively). Analysis of variance revealed 177 transcripts with different expression levels among the five strains compared. Five times more of these transcripts were differentiated between farmed parents and Tusket backcrosses (n = 53) than between Stewiacke backcrosses and their farmed parents (n = 11). Altered biological processes in backcrosses also differed between populations both in number and in the type of processes impacted (metabolism vs immunity). Over-dominant gene expression regulation in backcrosses varied considerably between populations (23% in Stewiacke vs 44% in Tusket). Hence, the consequences of introgression of farm genetic material on gene expression depended on population-specific genetic architectures. These results support the need to evaluate impacts of farm-wild genetic interactions at the population scale.
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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".