Limited genetic parallelism underlies recent, repeated incipient speciation in geographically proximate populations of an Arctic fish (Salvelinus alpinus)
Bibliographic record
Abstract
The genetic underpinnings of incipient speciation, including the genomic mechanisms which contribute to morphological and ecological differentiation and reproductive isolation, remain poorly understood. The repeated evolution of consistently, phenotypically distinct morphs of Arctic Charr (Salvelinus alpinus) within the Quaternary period offer an ideal model to study the repeatability of evolution at the genomic level. Sympatric morphs of Arctic Charr are found across this species' circumpolar distribution. However, the specific genetic mechanisms driving this morph differentiation are largely unknown despite the cultural and economic importance of the anadromous morph. We used a newly designed 87k SNP chip to investigate the character and consistency of the genomic differences among sympatric morphs within three recently deglaciated and geographically proximate lakes in Labrador, Canada. We found genetically distinct small and large morph Arctic Charr in all three lakes consistent with resident and anadromous morphs, respectively. A degree of reproductive isolation among sympatric morphs is likely given genome-wide distributions of outlier SNPs and high genome-wide FSTs. Across all lakes, outlier SNPs were largely non-overlapping suggesting a lack of genetic parallelism driving morph differentiation. Alternatively, several genes and paralogous copies of the same gene consistently differentiated morphs across multiple lakes suggesting their importance to the manifestation of morphs. Our results confirm the utility of Arctic Charr as a model for investigating the predictability of evolution and support the importance of both genetic parallelism and non-parallelism to the incipient speciation of Arctic Charr morphs.
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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 | 0.001 | 0.001 |
| 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 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".