Variation in the genomic basis of parallel phenotypic and ecological divergence in benthic and pelagic morphs of Icelandic Arctic charr (<i>Salvelinus alpinus</i>)
Bibliographic record
Abstract
Sympatric adaptive phenotypic divergence should be underlain by genomic differentiation between subpopulations. When divergence drives similar patterns of phenotypic and ecological variation within species we expect evolution to draw on common allelic variation. We investigated divergence histories and genomic signatures of adaptive divergence between benthic and pelagic morphs of Icelandic Arctic charr. Divergence histories for each of four populations were reconstructed using coalescent modelling and 14,187 single nucleotide polymorphisms. Sympatric divergence with continuous gene flow was supported in two populations while allopatric divergence with secondary contact was supported in one population; we could not differentiate between demographic models in the fourth population. We detected parallel patterns of phenotypic divergence along benthic-pelagic evolutionary trajectories among populations. Patterns of genomic differentiation between benthic and pelagic morphs were characterized by outlier loci in many narrow peaks of differentiation throughout the genome, which may reflect the eroding effects of gene flow on nearby neutral loci. We then used genome-wide association analyses to relate both phenotypic (body shape and size) and ecological (carbon and nitrogen stable isotopes) variation to patterns of genomic differentiation. Many peaks of genomic differentiation were associated with phenotypic and ecological variation in the three highly divergent populations, suggesting a genomic basis for adaptive divergence. We detected little evidence for a parallel genomic basis of differentiation as most regions and outlier loci were not shared among populations. Our results show that adaptive divergence can have varied genomic consequences in populations with relatively recent common origins, similar divergence histories, and parallel phenotypic divergence.
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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 | 0.000 |
| 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".