The mitochondrial genome of Endoconidiophora resinifera is intron rich
Bibliographic record
Abstract
Endoconidiophora resinifera (=Ceratocystis resinifera) is a blue-stain fungus that occurs on conifers. The data showed that the Endoconidiophora resinifera mitochondrial genome is one of the largest mitochondrial genomes (>220 kb) so far reported among members of the Ascomycota. An exceptional large number of introns (81) were noted and differences among the four strains were restricted to minor variations in intron numbers and a few indels and single nucleotide polymorphisms. The major differences among the four strains examined are due to size polymorphisms generated by the absence or presence of mitochondrial introns. Also, these mitochondrial genomes encode the largest cytochrome oxidase subunit 1 gene (47.5 kb) reported so far among the fungi. The large size for this gene again can be attributed to the large number of intron insertions. This study reports the first mitochondrial genome for the genus Endoconidiophora, previously members of this genus were assigned to Ceratocystis. The latter genus has recently undergone extensive taxonomic revisions and the mitochondrial genome might provide loci that could be applied as molecular markers assisting in the identification of taxa within this group of economically important fungi. The large mitochondrial genome also may provide some insight on mechanisms that can lead to mitochondrial genome expansion.
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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".