Genomic resources of <i>Ascidiella aspersa</i> and comparative analysis across tunicates reveal class-level features and evolutionary diversification
Bibliographic record
Abstract
Abstract Background Ascidiella aspersa is an invasive tunicate and one of the closest relatives of vertebrates. Despite its ecological nuisance, A. aspersa is anticipated to be a valuable model organism for developmental studies due to its remarkably transparent embryos. However, annotated genome assemblies and transcriptomic resources have not yet been fully established. Although several tunicate genomes have been sequenced, most lack annotations, and a comprehensive analysis across tunicates has not yet been conducted. Results We performed de novo genome assembly and transcriptome analysis of A. aspersa, producing a high-quality 306.5 Mb genome assembly. The transcriptome was derived from nine different organs of adults and embryos at six developmental stages. Ab initio and homology-based gene predictions identified 24,504 genes with a BUSCO score of 92.2%. Functional annotation was added for 18,636 genes in the model. To understand the relative features of this species among tunicates, we conducted genome-wide comparative analysis using publicly available data from 35 other tunicate genomes across three classes, five orders, and 12 families, thus constructing gene models for 27 species with BUSCO scores >80%. Overall, phylogenetic analysis revealed a new hypothesis regarding the relationships among Phlebobranchia and Aplousobranchia families. Gene duplication analysis showed distinct contractions of gene families in some taxa with losses of specific DNA repair related genes that were shared among Thaliacea—these may have contributed to their evolutionary diversification. Tunicate genomes exhibited a high level of variation in genomic GC content (28.0%–42.7%). A. aspersa has the highest GC content in coding regions and the third position of codons among tunicate species, with changes in codon usage bias differing from other Ascidiidae species. We also constructed an online comparative tunicate genome database (TUNOME), that provides functional annotations of gene models and ortholog analyses based on these genomic and transcriptomic data. Conclusions We constructed genomic resources for A. aspersa and another 35 tunicate gene models. Comparative analysis reveals a variety in tunicate species genomes and characterizes class-level features. Our resources are expected to be a foundation for experimental studies involving non-model tunicates and for comparative analysis among tunicate 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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".