Shared ancestral polymorphisms and chromosomal rearrangements as potential drivers of local adaptation in a marine fish
Bibliographic record
Abstract
Abstract Gene flow has tremendous importance for local adaptation, by influencing the fate of de novo mutations, maintaining standing genetic variation and driving adaptive introgression. Furthermore, structural variation as chromosomal rearrangements may facilitate adaptation despite high gene flow. However, our understanding of the evolutionary mechanisms impending or favouring local adaptation in the presence of gene flow is still limited to a restricted number of study systems. In this study, we examined how demographic history, shared ancestral polymorphism, and gene flow among glacial lineages contribute to local adaptation to sea conditions in a marine fish, the capelin ( Mallotus villosus ). We first assembled a 490‐Mbp draft genome of M. villosus to map our RAD sequence reads. Then, we used a large data set of genome‐wide single nucleotide polymorphisms (25,904 filtered SNPs) genotyped in 1,310 individuals collected from 31 spawning sites in the northwest Atlantic. We reconstructed the history of divergence among three glacial lineages and showed that they probably diverged from 3.8 to 1.8 million years ago and experienced secondary contacts. Within each lineage, our analyses provided evidence for large N e and high gene flow among spawning sites. Within the Northwest Atlantic lineage, we detected a polymorphic chromosomal rearrangement leading to the occurrence of three haplogroups. Genotype–environment associations revealed molecular signatures of local adaptation to environmental conditions prevailing at spawning sites. Our study also suggests that both shared polymorphisms among lineages, resulting from standing genetic variation or introgression, and chromosomal rearrangements may contribute to local adaptation in the presence of high gene flow.
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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 | 0.001 |
| 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 | 0.001 |
| 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".