Widespread occurrence of organelle genome-encoded 5S rRNAs including permuted molecules
Bibliographic record
Abstract
5S Ribosomal RNA (5S rRNA) is a universal component of ribosomes, and the corresponding gene is easily identified in archaeal, bacterial and nuclear genome sequences. However, organelle gene homologs (rrn5) appear to be absent from most mitochondrial and several chloroplast genomes. Here, we re-examine the distribution of organelle rrn5 by building mitochondrion- and plastid-specific covariance models (CMs) with which we screened organelle genome sequences. We not only recover all organelle rrn5 genes annotated in GenBank records, but also identify more than 50 previously unrecognized homologs in mitochondrial genomes of various stramenopiles, red algae, cryptomonads, malawimonads and apusozoans, and surprisingly, in the apicoplast (highly derived plastid) genomes of the coccidian pathogens Toxoplasma gondii and Eimeria tenella. Comparative modeling of RNA secondary structure reveals that mitochondrial 5S rRNAs from brown algae adopt a permuted triskelion shape that has not been seen elsewhere. Expression of the newly predicted rrn5 genes is confirmed experimentally in 10 instances, based on our own and published RNA-Seq data. This study establishes that particularly mitochondrial 5S rRNA has a much broader taxonomic distribution and a much larger structural variability than previously thought. The newly developed CMs will be made available via the Rfam database and the MFannot organelle genome annotator.
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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".