An unusual tRNAThr derived from tRNAHis reassigns in yeast mitochondria the CUN codons to threonine
Bibliographic record
Abstract
The standard genetic code is used by most living organisms, yet deviations have been observed in many genomes, suggesting that the genetic code has been evolving. In certain yeast mitochondria, CUN codons are reassigned from leucine to threonine, which requires an unusual tRNA(Thr) with an enlarged 8-nt anticodon loop ( ). To trace its evolutionary origin we performed a comprehensive phylogenetic analysis which revealed that evolved from yeast mitochondrial tRNA(His). To understand this tRNA identity change, we performed mutational and biochemical experiments. We show that Saccharomyces cerevisiae mitochondrial threonyl-tRNA synthetase (MST1) could attach threonine to both and the regular , but not to the wild-type tRNA(His). A loss of the first nucleotide (G(-1)) in tRNA(His) converts it to a substrate for MST1 with a K(m) value (0.7 μM) comparable to that of (0.3 μM), and addition of G(-1) to allows efficient histidylation by histidyl-tRNA synthetase. We also show that MST1 from Candida albicans, a yeast in which CUN codons remain assigned to leucine, could not threonylate , suggesting that MST1 has coevolved with . Our work provides the first clear example of a recent recoding event caused by alloacceptor tRNA gene recruitment.
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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".