Ophiostoma ulmi DNA naturally introgressed into an isolate of Ophiostoma novo-ulmi is clustered around pathogenicity and mating type loci
Bibliographic record
Abstract
The invasive fungal pathogensOphiostoma ulmiandO. novo-ulmihave caused two successive pandemics of Dutch elm disease since the beginning of the 20thcentury. In nature, the highly aggressiveO. novo-ulmimay hybridize with the less aggressiveO. ulmi. Growth rate and molecular analyses were conducted on an unusual, moderately aggressiveO. novo-ulmiisolate, AST27, carrying an introgressed pathogenicity gene,Pat1-m; on highly aggressiveO. novo-ulmiisolate H327; onO. ulmiisolates Q412T and W9; and on progeny from laboratory crosses between H327 and AST27. Genetic analysis indicated that thePat1andMat1(mating type) loci were in different linkage groups corresponding toO. novo-ulmiH327 chromosomes 1 and 2, respectively. Most of the molecular differences between the nuclear genomes of H327 and AST27 occurred in the vicinity ofPat1andMat1. In addition, two putative quanti-tative trait loci,Mgr1andMgr2, which influence mycelial growth rate at 21°C and 28°C, the optima forO. novo-ulmiandO. ulmi, were linked toMat1andPat1, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".