RNA-seq analysis of the <i>C. briggsae</i> transcriptome
Bibliographic record
Abstract
Curation of a high-quality gene set is the critical first step in genome research, enabling subsequent analyses such as ortholog assignment, cis-regulatory element finding, and synteny detection. In this project, we have reannotated the genome of Caenorhabditis briggsae, the best studied sister species of the model organism Caenorhabditis elegans. First, we applied a homology-based gene predictor genBlastG to annotate the C. briggsae genome. We then validated and further improved the C. briggsae gene annotation through RNA-seq analysis of the C. briggsae transcriptome, which resulted in the first validated C. briggsae gene set (23,159 genes), among which 7347 genes (33.9% of all genes with introns) have all of their introns confirmed. Most genes (14,812, or 68.3%) have at least one intron validated, compared with only 3.9% in the most recent WormBase release (WS228). Of all introns in the revised gene set (103,083), 61,503 (60.1%) have been confirmed. Additionally, we have identified numerous trans-splicing leaders (SL1 and SL2 variants) in C. briggsae, leading to the first genome-wide annotation of operons in C. briggsae (1105 operons). The majority of the annotated operons (564, or 51.0%) are perfectly conserved in C. elegans, with an additional 345 operons (or 31.2%) somewhat divergent. Additionally, RNA-seq analysis revealed over 10 thousand small-size assembly errors in the current C. briggsae reference genome that can be readily corrected. The revised C. briggsae genome annotation represents a solid platform for comparative genomics analysis and evolutionary studies of Caenorhabditis 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".