Towards map-based cloning of FB_Mfu10: identification of a receptor-like kinase candidate gene underlying the Malus fusca fire blight resistance locus on linkage group 10
Bibliographic record
Abstract
Breeding for resistance against the destructive fire blight disease of apples is the most sustainable strategy to control the menace of this disease, and has become increasingly important in European apple breeding programs. Since most cultivars are susceptible, wild accessions have been explored for resistance with quantitative trait loci detected in a few wild species. Fire blight resistance of Malus fusca was described following phenotypic evaluations with a C-type strain of Erwinia amylovora , Ea222_JKI, and the detection of a major QTL on chromosome 10 ( Mfu10 ) of this crabapple. The stability of the resistance of M . fusca and Mfu10 has been evaluated using two other strains, the highly aggressive Canadian S-type strain—Ea3049, and the avrRpt2 EA mutant—ZYRKD3-1, both of which overcome the resistance of Malus × robusta 5, a wild species accession with an already described fire blight resistance gene. To pave the way for positional cloning of the underlying fire blight resistance gene of M. fusca , we have fine mapped the QTL region on linkage group 10 using 1888 individuals and 23 newly developed molecular markers, thus delimiting the interval of interest to 0.33 cM between markers FR39G5T7xT7y/FR24N24RP and FRMf7358424/FR46H22. Tightly linked SSR markers are suitable for marker-assisted selection in breeding programs. Furthermore, a bacterial artificial chromosome (BAC) clone spanning FB_Mfu10 region was isolated and sequenced. One putative fire blight resistance candidate gene of M. fusca was predicted on the sequence of BAC 46H22 within the resistance region that encodes B-lectin and serine/threonine kinase domains.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".