Revealing the evolutionary history and contemporary population structure of Pacific salmon in the Fraser River through genome resequencing
Bibliographic record
Abstract
The Fraser River once supported massive salmon returns. However, over the last century, the largest returns have consistently been less than half of the recorded historical maximum. There is substantial interest from surrounding communities and governments to increase salmon returns for both human use and functional ecosystems. To generate resources for this endeavor, we resequenced genomes of Chinook (Oncorhynchus tshawytscha), coho (Oncorhynchus kisutch), and sockeye salmon (Oncorhynchus nerka) from the Fraser River at moderate coverage (∼16×). A total of 954 resequenced genomes were analyzed, with 681 collected specifically for this study from tissues sampled between 1997 and 2021. An additional 273 were collected from previous studies. At the species level, Chinook salmon appeared to have 1.6-2.1× more SNPs than coho or sockeye salmon, respectively. This difference may be attributable to large historical declines of coho and sockeye salmon. At the population level, 3 Fraser River genetic groups were identified for each species using principal component and admixture analyses. These were consistent with previous research and supports the continued use of these groups in conservation and management efforts. Environmental factors and a migration barrier were identified as major factors influencing the boundaries of these genetic groups. Additionally, 20 potentially adaptive loci were identified among the genetic groups. This information may be valuable in new management and conservation efforts. Furthermore, the resequenced genomes are an important resource for contemporary genomics research on Fraser River salmon and have been made publicly available.
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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 | 0.001 | 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".