Improved genome assembly and evidence-based global gene model set for the chordate Ciona intestinalis: new insight into intron and operon populations
Bibliographic record
Abstract
BACKGROUND: The draft genome sequence of the ascidian Ciona intestinalis, along with associated gene models, has been a valuable research resource. However, recently accumulated expressed sequence tag (EST)/cDNA data have revealed numerous inconsistencies with the gene models due in part to intrinsic limitations in gene prediction programs and in part to the fragmented nature of the assembly. RESULTS: We have prepared a less-fragmented assembly on the basis of scaffold-joining guided by paired-end EST and bacterial artificial chromosome (BAC) sequences, and BAC chromosomal in situ hybridization data. The new assembly (115.2 Mb) is similar in length to the initial assembly (116.7 Mb) but contains 1,272 (approximately 50%) fewer scaffolds. The largest scaffold in the new assembly incorporates 95 initial-assembly scaffolds. In conjunction with the new assembly, we have prepared a greatly improved global gene model set strictly correlated with the extensive currently available EST data. The total gene number (15,254) is similar to that of the initial set (15,582), but the new set includes 3,330 models at genomic sites where none were present in the initial set, and 1,779 models that represent fusions of multiple previously incomplete models. In approximately half, 5'-ends were precisely mapped using 5'-full-length ESTs, an important refinement even in otherwise unchanged models. CONCLUSION: Using these new resources, we identify a population of non-canonical (non-GT-AG) introns and also find that approximately 20% of Ciona genes reside in operons and that operons contain a high proportion of single-exon genes. Thus, the present dataset provides an opportunity to analyze the Ciona genome much more precisely than ever.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".