Cloning of disease-resistance homologues in end sequences of BAC clones linked to<i>Fom-2</i>, a gene conferring resistance to<i>Fusarium</i>wilt in melon (<i>Cucumis melo</i>L.)
Bibliographic record
Abstract
Disease resistance has not yet been characterized at the molecular level in cucurbits, a group of high-value, nutritious, horticultural plants. Previously, we genetically mapped the Fom-2 gene that confers resistance to Fusarium wilt races 0 and I of melon. In this paper, two cosegregating codominant markers (AM, AFLP marker; FM, Fusarium marker) were used to screen a melon bacterial artificial chromosome (BAC) library. Identified clones were fingerprinted and end sequenced. Fingerprinting analysis showed that clones identified by each marker assembled into two separate contigs at high stringency. GenBank searches produced matches to leucine-rich repeats (LRRs) of resistance genes (R genes); to retroelements and to cellulose synthase in clones identified by FM; and to nucleotide-binding sites (NBSs) of R genes, retroelements, and cytochrome P-450 in clones identified by AM. A 6.5-kb fragment containing both NBS and LRR sequences was found to share high homology to TIR (Toll-interleukin-1 receptor)-NBS-LRR R genes, such as N, with 42% identity and 58% similarity in the TIR-NBS and LRR regions. The sequence information may be useful for identifying NBS-LRR class of R genes in other cucurbits.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".