Genome-wide Analysis of Drosophila Circular RNAs Reveals Their Structural and Sequence Properties and Age-Dependent Neural Accumulation
Bibliographic record
Abstract
Circularization was recently recognized to broadly expand transcriptome complexity. Here, we exploit massive Drosophila total RNA-sequencing data, >5 billion paired-end reads from >100 libraries covering diverse developmental stages, tissues, and cultured cells, to rigorously annotate >2,500 fruit fly circular RNAs. These mostly derive from back-splicing of protein-coding genes and lack poly(A) tails, and the circularization of hundreds of genes is conserved across multiple Drosophila species. We elucidate structural and sequence properties of Drosophila circular RNAs, which exhibit commonalities and distinctions from mammalian circles. Notably, Drosophila circular RNAs harbor >1,000 well-conserved canonical miRNA seed matches, especially within coding regions, and coding conserved miRNA sites reside preferentially within circularized exons. Finally, we analyze the developmental and tissue specificity of circular RNAs and note their preferred derivation from neural genes and enhanced accumulation in neural tissues. Interestingly, circular isoforms increase substantially relative to linear isoforms during CNS aging and constitute an aging biomarker.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".