Investigating genomic and phenotypic parallelism between piscivorous and planktivorous lake trout (<i>Salvelinus namaycush</i>) ecotypes by means of<scp>RAD</scp>seq and morphometrics analyses
Bibliographic record
Abstract
Repeated adaptive ecological diversification has commonly been reported in fish and has often been associated with trophic niche diversity. The main goal of this study was to investigate the extent of parallelism in the genomic and phenotypic divergence between piscivorous and planktivorous lake trout ecotypes from Laurentian Shield lakes, Canada. This was achieved by documenting the extent of morphological differentiation using geometric morphometrics and linear measurements as well as the pattern of genomic divergence by means of RADseq genotyping (3925 filtered SNPs) in 12 lakes. Our results indicate that the two ecotypes evolved distinct body shape and several linear measurements in parallel. Neutral genetic differentiation was pronounced between all isolated populations (Mean FST = 0.433), indicating no or very limited migration and pronounced genetic drift. Significant genetic differentiation also suggested partial reproductive isolation between ecotypes in the two lakes where they are found in sympatry. Combining different outlier detection methods, we identified 48 SNPs putatively under divergent selection between ecotypes, among which 10 could be annotated and related to functions such as developmental processes and ionic regulation. Finally, our results indicate that parallel morphological divergence is accompanied by both parallel and nonparallel genomic divergence, which is associated with the use of different trophic niches between ecotypes. The results are also discussed in the context of management and conservation of this highly exploited species throughout northern North America.
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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 | 0.001 | 0.001 |
| 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".