Characterization of the mitochondrial genomes for Ophiostoma ips and related taxa from various geographic origins and related species: large intron-rich genomes and complex intron arrangements
Bibliographic record
Abstract
The Ophiostomatales are of economic concern, as many are blue-stain fungi and some are plant pathogens. The mitogenomes of members assigned to this order exhibit size polymorphism despite having highly conserved gene order, owing to the variable number of introns and intron insertion sites. In this work, eleven blue-stain fungi, including nine strains of Ophiostoma ips with a varied distribution across North America and New Zealand, were sequenced and compared with other members of the Ophiostomatales . A pan-mitogenome intron landscape has been prepared to demonstrate the distribution of the mobile genetic elements and to provide insight into the evolutionary dynamics of introns among members of this group of fungi. The size variation among these mitogenomes (from about 23.8 kb to 152 kb) shows high correlation to the presence and absence of introns. Examples of complex or nested introns composed of two or three intron modules have been observed in some O. ips strains. RNA-seq data suggests possible splicing pathways with regard to resolving these complex introns. Mitochondrial DNA and RNA data for O. ips provides the basis for future studies relating to gene annotation, alternative splicing, evolutionary intron dynamics, and taxonomic investigations for members of the Ophiostomatales .
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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) | 0.001 | 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".