Sequencing, de novo annotation and analysis of the first Anguilla anguilla transcriptome: EeelBase opens new perspectives for the study of the critically endangered european eel
Bibliographic record
Abstract
BACKGROUND: Once highly abundant, the European eel (Anguilla anguilla L.; Anguillidae; Teleostei) is considered to be critically endangered and on the verge of extinction, as the stock has declined by 90-99% since the 1980s. Yet, the species is poorly characterized at molecular level with little sequence information available in public databases. RESULTS: The first European eel transcriptome was obtained by 454 FLX Titanium sequencing of a normalized cDNA library, produced from a pool of 18 glass eels (juveniles) from the French Atlantic coast and two sites in the Mediterranean coast. Over 310,000 reads were assembled in a total of 19,631 transcribed contigs, with an average length of 531 nucleotides. Overall 36% of the contigs were annotated to known protein/nucleotide sequences and 35 putative miRNA identified. CONCLUSIONS: This study represents the first transcriptome analysis for a critically endangered species. EeelBase, a dedicated database of annotated transcriptome sequences of the European eel is freely available at http://compgen.bio.unipd.it/eeelbase. Considering the multiple factors potentially involved in the decline of the European eel, including anthropogenic factors such as pollution and human-introduced diseases, our results will provide a rich source of data to discover and identify new genes, characterize gene expression, as well as for identification of genetic markers scattered across the genome to be used in various applications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".