A one-megabase physical map provides insights on gene organization in the enormous mitochondrial genome of cucumber
Bibliographic record
Abstract
Cucumber (Cucumis sativus) has one of the largest mitochondrial genomes known among all eukaryotes, due in part to the accumulation of short 20 to 60 bp repetitive DNA motifs. Recombination among these repetitive DNAs produces rearrangements affecting organization and expression of mitochondrial genes. To more efficiently identify rearrangements in the cucumber mitochondrial DNA, we built two nonoverlapping 800 and 220 kb BAC contigs and assigned major mitochondrial genes to these BACs. Polymorphism carried on the largest BAC contig was used to confirm paternal transmission. Mitochondrial genes were distributed across BACs and physically distant, although occasional clustering was observed. Introns in the nad1, nad4, and nad7 genes were larger than those reported in other plants, due in part to accumulation of short repetitive DNAs and indicating that increased intron sizes contributed to mitochondrial genome expansion in cucumber. Mitochondrial genes atp6 and atp9 are physically close to each other and cotranscribed. These physical contigs will be useful for eventual sequencing of the cucumber mitochondrial DNA, which can be exploited to more efficiently screen for unique rearrangements affecting mitochondrial gene expression.
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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 | 0.000 | 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) | 0.004 | 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".