Discovery and characterization of single nucleotide polymorphisms in Chinook salmon, <i>Oncorhynchus tshawytscha</i>
Bibliographic record
Abstract
Molecular population genetics of non-model organisms has been dominated by the use of microsatellite loci over the last two decades. The availability of extensive genomic resources for many species is contributing to a transition to the use of single nucleotide polymorphisms (SNPs) for the study of many natural populations. Here we describe the discovery of a large number of SNPs in Chinook salmon, one of the world's most important fishery species, through large-scale Sanger sequencing of expressed sequence tag (EST) regions. More than 3 Mb of sequence was collected in a survey of variation in almost 132 kb of unique genic regions, from 225 separate ESTs, in a diverse ascertainment panel of 24 salmon. This survey yielded 117 TaqMan (5' nuclease) assays, almost all from separate ESTs, which were validated in population samples from five major stocks of salmon from the three largest basins on the Pacific coast of the contiguous United States: the Sacramento, Klamath and Columbia Rivers. The proportion of these loci that was variable in each of these stocks ranged from 86.3% to 90.6% and the mean minor allele frequency ranged from 0.194 to 0.236. There was substantial differentiation between populations with these markers, with a mean F(ST) estimate of 0.107, and values for individual loci ranging from 0 to 0.592. This substantial polymorphism and population-specific differentiation indicates that these markers will be broadly useful, including for both pedigree reconstruction and genetic stock identification applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".