Comprehensive EST analysis of Atlantic halibut (Hippoglossus hippoglossus), a commercially relevant aquaculture species
Bibliographic record
Abstract
BACKGROUND: An essential first step in the genomic characterisation of a new species, in this case Atlantic halibut (Hippoglossus hippoglossus), is the generation of EST information. This forms the basis for subsequent microarray design, SNP detection and the placement of novel markers on genetic linkage maps. RESULTS: Normalised directional cDNA libraries were constructed from five different larval stages (hatching, mouth-opening, midway to metamorphosis, premetamorphosis, and post-metamorphosis) and eight different adult tissues (testis, ovary, liver, head kidney, spleen, skin, gill, and intestine). Recombination efficiency of the libraries ranged from 91-98% and insert size averaged 1.4 kb. Approximately 1000 clones were sequenced from the 5'-end of each library and after trimming, 12675 good sequences were obtained. Redundancy within each library was very low and assembly of the entire EST collection into contigs resulted in 7738 unique sequences of which 6722 (87%) had matches in Genbank. Removal of ESTs and contigs that originated from bacteria or food organisms resulted in a total of 7710 unique halibut sequences. CONCLUSION: A Unigene collection of 7710 functionally annotated ESTs has been assembled from Atlantic halibut. These have been incorporated into a publicly available, searchable database and form the basis for an oligonucleotide microarray that can be used as a tool to study gene expression in this economically important aquacultured fish.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".