Identification and Structural Characterization of Nucleus-encoded Transfer RNAs Imported into Wheat Mitochondria
Bibliographic record
Abstract
Despite its large size (200-2400 kilobase pairs), the mitochondrial genome of angiosperms does not encode the minimal set of tRNAs required to support mitochondrial protein synthesis. Here we report the identification of cytosolic-like tRNAs in wheat mitochondria using a method involving quantitative hybridization to distinguish among three tRNA classes: (i) those encoded by mitochondrial DNA (mtDNA) and localized in mitochondria, (ii) those encoded by nuclear DNA and located in the cytosol, and (iii) those encoded by nuclear DNA and found in both the cytosol and mitochondria. The latter class comprises tRNA species that are considered to be imported into mitochondria to compensate for the deficiency of mtDNA-encoded tRNAs. In a comprehensive survey of the wheat mitochondrial tRNA population, we identified 14 such imported tRNAs, the structural characterization of which is presented here. These imported tRNAs complement 16 mtDNA-encoded tRNAs, for a total of at least 30 distinct tRNA species in wheat mitochondria. Considering differences in the set of mtDNA-encoded and imported tRNAs in the mitochondria of various land plants, the import system must be able to adapt relatively rapidly over evolutionary time with regard to the particular cytosolic-like tRNAs that are brought into mitochondria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".