Genome-wide analysis to investigate patterns of ecotype divergence, population structure and life history changes in deep-spawning sockeye salmon, Oncorhynchus nerka
Bibliographic record
Abstract
Sockeye salmon (Oncorhynchus nerka) have been a classic study system for investigating ecotype divergence due to their tremendous life history variation. Multiple independent lineages of freshwater O. nerka (kokanee) have evolved from anadromous sockeye, and these migratory forms are further divided into reproductive ecotypes, depending on spawning location (shore-, stream- and deep-spawners). Deep-spawning O. nerka in Canada and Japan share unique phenotypic traits, but little is known about the origin and genomic basis of this ecotype. Here, we conducted genome-wide analyses of deep-spawning O. nerka on multiple scales, from regional populations in British Columbia, Canada, to those that span the pan Pacific distribution. First, we analyzed the Alouette Lake (British Columbia) O. nerka population, which (a) consists of both migrant and resident individuals, and (b) is the only known O. nerka population where migrants exhibit deep-spawning behaviour, leading to questions regarding the true ecotype of this population. To investigate the genomic basis of life history variation in this system, we collected SNP data (n = 7,709) for migrant and resident Alouette O. nerka (n = 163) and analyzed these samples relative to each other and O. nerka (n = 149) from known anadromous sockeye salmon and kokanee populations across the Fraser River drainage. Population structure analyses revealed five distinct clusters, primarily associated with geography, and no evidence for differentiation between resident and migrant Alouette O. nerka at the neutral loci. However, we identified eight high-confidence outlier loci divergent between migrant and resident Alouette O. nerka that were located on sex chromosomes, suggesting an association between migratory behaviour and sex in this system. We conclude that Alouette O. nerka likely represents a single stock best characterized as land-locked sockeye salmon, with individuals that retain the ability to migrate. Second, we genotyped deep- and stream-spawning kokanee (n = 167) from Canada and Japan at 9,721 SNPs, revealing a low number of shared ecotype-associated outliers between the two regions. Unlike in British Columbia, population clustering within Japan was best explained by translocation history. Taken together, these data suggest that evolution of the deep-spawning ecotype on two continents likely proceeded through different genetic pathways.
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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 | 0.003 |
| Science and technology studies | 0.001 | 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".