Assembly and comparative analysis of the complete mitochondrial genome of tea-scented China rose
Bibliographic record
Abstract
Plant mitochondrial (mt) genomes enable better understanding of cellular processes and phylogenetic relationships. Tea-scented China rose ‘Hume's Blush Tea-scented China’ is the ancestor of the modern hybrid tea rose and has had an important and lasting influence on the breeding of the modern horticultural rose, but a comprehensive description of its mt genome is not yet available. In this study, mature leaves were used to determine the sequence of the rose mt genome. The mt genome of ‘Hume's Blush Tea-scented China’ is a circular sequence 277 730 bp in length and includes 30 protein-coding genes, 19 tRNA genes, and 3 rRNA genes. We analyzed repeat sequences, codon preferences, and RNA editing processes. In addition, we detected the transfer of 25 chloroplast genes to the mt genome, indicating intracellular genes transferred frequently from chloroplasts to mitochondria in ‘Hume's Blush Tea-scented China’. The phylogenetic analysis of the ‘Hume's Blush Tea-scented China’ mt genome and those of 26 other plant groups reflects its taxonomic status. The Ka/Ks of most genes was less than 1, indicating that most coding genes underwent negative selection, while pi was greater than 0.01, confirming highly diverse genetic variation. This work lays a foundation for future investigation of genetic variation in ‘Hume's Blush Tea-scented China’.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".