Comparative mapping of expressed sequence tags containing microsatellites in rainbow trout (Oncorhynchus mykiss)
Bibliographic record
Abstract
BACKGROUND: Comparative genomics, through the integration of genetic maps from species of interest with whole genome sequences of other species, will facilitate the identification of genes affecting phenotypes of interest. The development of microsatellite markers from expressed sequence tags will serve to increase marker densities on current salmonid genetic maps and initiate in silico comparative maps with species whose genomes have been fully sequenced. RESULTS: Eighty-nine polymorphic microsatellite markers were generated for rainbow trout of which at least 74 amplify in other salmonids. Fifty-five have been associated with functional annotation and 30 were mapped on existing genetic maps. Homologous sequences were identified for 20 of the EST containing microsatellites to identify comparative assignments within the tetraodon, mouse, and/or human genomes. CONCLUSION: The addition of microsatellite markers constructed from expressed sequence tag data will facilitate the development of high-density genetic maps for rainbow trout and comparative maps with other salmonids and better studied species.
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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".