Near‐complete genome assembly and annotation of the yellow drum (<i>Nibea albiflora</i>) provide insights into population and evolutionary characteristics of this species
Bibliographic record
Abstract
Abstract Yellow drum (Nibea albiflora) is an important fish species in capture fishery and aquaculture in East Asia. We herein report the first and near‐complete genome assembly of an ultra‐homologous gynogenic female yellow drum using Illumina short sequencing reads. In summary, a total of 154.2 Gb of raw reads were generated via whole‐genome sequencing and were assembled to 565.3 Mb genome with a contig N50 size of 50.3 kb and scaffold N50 size of 2.2 Mb (BUSCO completeness of 97.7%), accounting for 97.3%–98.6% of the estimated genome size of this fish. We further identified 22,448 genes using combined methods of ab initio prediction, RNAseq annotation, and protein homology searching, of which 21,614 (96.3%) were functionally annotated in NCBI nr, trEMBL, SwissProt, and KOG databases. We also investigated the nucleotide diversity (around 1/390) of aquacultured individuals and found the genetic diversity of the aquacultured population decreased due to inbreeding. Evolutionary analyses illustrated significantly expanded and extracted gene families, such as myosin and sodium: neurotransmitter symporter (SNF), could help explain swimming motility of yellow drum. The presented genome will be an important resource for future studies on population genetics, conservation, understanding of evolutionary history and genetic breeding of the yellow drum and other Nibea species.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.002 |
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".