The Between-Population Genetic Architecture of Growth, Maturation, and Plasticity in Atlantic Salmon
Bibliographic record
Abstract
The between-population genetic architecture for growth and maturation has not been examined in detail for many animal species despite its central importance in understanding hybrid fitness. We studied the genetic architecture of population divergence in: (i) maturation probabilities at the same age; (ii) size at age and growth, while accounting for maturity status and sex; and (iii) growth plasticity in response to environmental factors, using divergent wild and domesticated Atlantic salmon (Salmo salar). Our work examined two populations and their multigenerational hybrids in a common experimental arrangement in which salinity and quantity of suspended sediments were manipulated to mimic naturally occurring environmental variation. Average specific growth rates across environments differed among crosses, maturity groups, and cross-by-maturity groups, but a growth-rate reduction in the presence of suspended sediments was equal for all groups. Our results revealed both additive and nonadditive outbreeding effects for size at age and for growth rates that differed with life stage, as well as the presence of different sex- and size-specific maturation probabilities between populations. The major implication of our work is that estimates of the genetic architecture of growth and maturation can be biased if one does not simultaneously account for temporal changes in growth and for different maturation probabilities between populations. Namely, these correlated traits interact differently within each population and between sexes and among generations, due to nonadditive effects and a level of independence in the genetic control for traits. Our results emphasize the challenges to investigating and predicting phenotypic changes resulting from between-population outbreeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".