A draft genome assembly of the Chinese sillago (<i>Sillago sinica</i>), the first reference genome for Sillaginidae fishes
Bibliographic record
Abstract
Background: Sillaginidae, also known as smelt-whitings, is a family of benthic coastal marine fishes in the Indo-West Pacific that have high ecological and economic importance. Many Sillaginidae species, including the Chinese sillago (Sillago sinica), have been recently described in China, providing valuable material to analyze genetic diversification of the family Sillaginidae. Here, we constructed a reference genome for the Chinese sillago, with the aim to set up a platform for comparative analysis of all species in this family. Findings: Using the single-molecule real-time DNA sequencing platform Pacific Biosciences (PacBio) Sequel, we generated ∼27.3 Gb genomic DNA sequences for the Chinese sillago. We reconstructed a genome assembly of 534 Mb using a strategy that takes advantage of complementary strengths of two genome assembly programs, Canu and FALCON. The genome size was consistent with the estimated genome size based on k-mer analysis. The assembled genome consisted of 802 contigs with a contig N50 length of 2.6 Mb. We annotated 22,122 protein-coding genes in the Chinese sillago genomes using a de novo method as well as RNA sequencing data and homologies to other teleosts. According to the phylogenetic analysis using protein-coding genes, the Chinese sillago is closely related to Larimichthys crocea and Dicentrarchus labrax and diverged from their ancestor around 69.5-82.6 million years ago. Conclusions: Using long reads generated with PacBio sequencing technology, we have built a draft genome assembly for the Chinese sillago, which is the first reference genome for Sillaginidae species. This genome assembly sets a stage for comparative analysis of the diversification and adaptation of fishes in Sillaginidae.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".