RNA-level unscrambling of fragmented genes in <i> <i>Diplonema</i> </i> mitochondria
Bibliographic record
Abstract
We previously reported a unique genome with systematically fragmented genes and gene pieces dispersed across numerous circular chromosomes, occurring in mitochondria of diplonemids. Genes are split into up to 12 short fragments (modules), which are separately transcribed and joined in a way that differs from known trans-splicing. Further, cox1 mRNA includes six non-encoded uridines indicating RNA editing. In the absence of recognizable cis-elements, we postulated that trans-splicing and RNA editing are directed by trans-acting molecules. Here, we provide insight into the post-transcriptional processes by investigating transcription, RNA processing, trans-splicing and RNA editing in cox1 and at a newly discovered site in cob. We show that module precursor transcripts are up to several thousand nt long and processed accurately at their 5' and 3' termini to yield the short coding-only regions. Processing at 5' and 3' ends occurs independently, and a processed terminus engages in trans-splicing even if the module's other terminus is yet unprocessed. Moreover, only cognate module transcripts join, though without directionality. In contrast, module transcripts requiring RNA editing only trans-splice when editing is completed. Finally, experimental and computational analyses suggest the existence of RNA trans-factors with the potential for guiding both trans-splicing and RNA editing.
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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) | 0.001 | 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".