Mitochondrial genome of Quercus chenii: genomic features and evolutionary implications
Bibliographic record
Abstract
Recent advances in high-throughput sequencing have enabled detailed characterization of plant mitochondrial genomes. Here, we assembled and analyzed the mitochondrial genome of Quercus chenii Nakai, a key oak species in Fagaceae, using Illumina NovaSeq6000. The genome consists of a 364,958 bp linear and a 53,677 bp circular chromosome, totaling 418,635 bp with a GC content of 45.6%. Repeat-rich regions (210–250 and 300–340 kb) may facilitate structural rearrangements, while extensive RNA editing-particularly in nad4 and ccmF-likely enhances protein functionality and mitochondrial adaptability. Comparative collinearity analysis showed high structural conservation with Q. acutissima Carruth. (90.92%) but marked divergence from Fagus sylvatica L. (35.80%), suggesting lineage-specific rearrangements. Phylogenetic analysis based on the mitochondrial genome supports the same placement of Q. chenii within Fagaceae as that derived from the chloroplast genome. The Ka/Ks analysis across Fagaceae mitochondrial genomes revealed strong conservation of core genes, with adaptive variations in energy metabolism-related genes, suggesting functional divergence linked to metabolic optimization under environmental stress. These findings highlight the distinct evolutionary strategies of mitochondrial and chloroplast genomes: the former optimizing energy production, while the latter fine-tunes photosynthesis and stress responses. Comparison analysis with the chloroplast genome further revealed both conserved (psbT and psbC) and divergent (ndhD and ndhF) genes, implying potential historical gene transfer events. Together, these findings highlight the dynamic yet conserved nature of the Q. chenii mitochondrial genome and provide new insights into organellar genome evolution, structural plasticity, and adaptive mechanisms within the Fagaceae family.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".