Large Haplotypes Linked to Climate and Life History Variation in Divergent Lineages of Atlantic Salmon ( <scp> <i>Salmo salar</i> </scp> )
Bibliographic record
Abstract
Advances in sequencing are revealing that linked genomic architectures, enabling the evolution of co-adapted alleles at multiple loci, often shape complex phenotypes. Several recent studies have identified such architectures (e.g., chromosomal rearrangements and supergenes) contributing to adaptation or divergence across diverse species, from plants to mammals. Specifically, within Atlantic salmon (Salmo salar ), genomic studies are revealing large haplotypes and structural variants that may underpin local adaptation in the species. Using data from > 4000 individuals from 134 locations spanning the North Atlantic Ocean, we identify a large (~3 Mbp) genomic region on Ssa18 showing patterns of differentiation and linkage disequilibrium (LD) indicative of a large haplotype block containing three divergent haplotypes (herein A, B and C haplotypes). In Europe, haplotypes A and B were common, whereas A and C were more common within North America, suggesting a shared 'ancestral' A haplotype, with different continent-specific alternative haplotypes. Data support independent origins of divergent haplotypes in each continent, as well as signals of trans-oceanic introgression of haplotypes. Haplotype frequency is strongly associated with latitude, climate and life history (smolt age); however, the strength and direction of these relationships vary across continents. Overall, our analyses were consistent with other studies that identify chromosomal rearrangements; however, long-read sequence data did not find evidence of a structural variant, and instead an ancestral fusion may explain the formation and maintenance of the observed haplotypes. Our study contributes to ongoing efforts to understand the evolutionary role of linked genomic architecture in Atlantic salmon and its significance in salmonid diversification.
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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".