An Integrated Approach to Gene Discovery and Marker Development in Atlantic Cod (Gadus morhua)
Bibliographic record
Abstract
Atlantic cod is a species that has been overexploited by the capture fishery. Programs to domesticate this species are underway in several countries, including Canada, to provide an alternative route for production. Selective breeding programs have been successfully applied in the domestication of other species, with genomics-based approaches used to augment conventional methods of animal production in recent years. Genomics tools, such as gene sequences and sets of variable markers, also have the potential to enhance and accelerate selective breeding programs in aquaculture, and to provide better monitoring tools to ensure that wild cod populations are well managed. We describe the generation of significant genomics resources for Atlantic cod through an integrated genomics/selective breeding approach. These include 158,877 expressed sequence tags (ESTs), a set of annotated putative transcripts and several thousand single nucleotide polymorphism markers that were developed from, and have been shown to be highly variable in, fish enrolled in two selective breeding programs. Our EST collection was generated from various tissues and life cycle stages. In some cases, tissues from which libraries were generated were isolated from fish exposed to stressors, including elevated temperature, or antigen stimulation (bacterial and viral) to enrich for transcripts that are involved in these response pathways. The genomics resources described here support the developing aquaculture industry, enabling the application of molecular markers within selective breeding programs. Marker sets should also find widespread application in fisheries management.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".