Identification of quantitative trait loci for powdery mildew resistance in highly resistant cucumber (<i>Cucumis sativus</i> L.) using ddRAD-seq analysis
Bibliographic record
Abstract
L.). Cucumber parental line 'Kyuri Chukanbohon Nou 5 Go', developed from weedy cucumber line CS-PMR1, is highly resistant to powdery mildew and is promising breeding material. We performed quantitative trait locus (QTL) analysis using double-digest restriction-site-associated DNA sequencing (ddRAD-Seq) in a population from a cross between 'Kyuri Chukanbohon Nou 5 Go' and the Japanese native cultivar 'Kaga-aonaga-fushinari', which is susceptible to powdery mildew. The resistance of the population and its parents was evaluated using leaf disc assays and image analysis. We detected one major QTL on Chr. 5 that was effective at both 20°C and 25°C and one minor QTL on Chr. 1 effective at 20°C. We detected two additional QTLs in subpopulation: one on Chr. 3 effective at 20°C and one on Chr. 5 effective at both 20°C and 25°C in a position different from the major QTL. The resistance alleles at all four QTLs were contributed by 'Kyuri Chukanbohon Nou 5 Go'. The results of this study can be used to develop practical DNA markers tightly linked to genes for powdery mildew resistance.
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) | 0.002 | 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".