Gene Loss and Error-Prone RNA Editing in the Mitochondrion of <i>Perkinsela</i> , an Endosymbiotic Kinetoplastid
Bibliographic record
Abstract
UNLABELLED: Perkinsela is an enigmatic early-branching kinetoplastid protist that lives as an obligate endosymbiont inside Paramoeba (Amoebozoa). We have sequenced the highly reduced mitochondrial genome of Perkinsela, which possesses only six protein-coding genes (cox1, cox2, cox3, cob, atp6, and rps12), despite the fact that the organelle itself contains more DNA than is present in either the host or endosymbiont nuclear genomes. An in silico analysis of two Perkinsela strains showed that mitochondrial RNA editing and processing machineries typical of kinetoplastid flagellates are generally conserved, and all mitochondrial transcripts undergo U-insertion/deletion editing. Canonical kinetoplastid mitochondrial ribosomes are also present. We have developed software tools for accurate and exhaustive mapping of transcriptome sequencing (RNA-seq) reads with extensive U-insertions/deletions, which allows detailed investigation of RNA editing via deep sequencing. With these methods, we show that up to 50% of reads for a given edited region contain errors of the editing system or, less likely, correspond to alternatively edited transcripts. IMPORTANCE: Uridine insertion/deletion-type RNA editing, which occurs in the mitochondrion of kinetoplastid protists, has been well-studied in the model parasite genera Trypanosoma, Leishmania, and Crithidia. Perkinsela provides a unique opportunity to broaden our knowledge of RNA editing machinery from an evolutionary perspective, as it represents the earliest kinetoplastid branch and is an obligatory endosymbiont with extensive reductive trends. Interestingly, up to 50% of mitochondrial transcripts in Perkinsela contain errors. Our study was complemented by use of newly developed software designed for accurate mapping of extensively edited RNA-seq reads obtained by deep sequencing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".