Molecular mapping of novel genes controlling<i>Fusarium</i>head blight resistance and deoxynivalenol accumulation in spring wheat
Bibliographic record
Abstract
Fusarium head blight of wheat is an extremely damaging disease, causing severe losses in seed yield and quality. The objective of the current study was to examine and characterize alternate sources of resistance to Fusarium head blight (FHB). Ninety-one F1-derived doubled haploid lines from the cross Triticum aestivum 'Wuhan-1' x Triticum aestivum 'Maringa' were examined for disease reaction to Fusarium graminearum by single-floret injection in replicated greenhouse trials and by spray inoculation in replicated field trials. Field and greenhouse experiments were also used to collect agronomic and spike morphology characteristics. Seed samples from field plots were used for deoxynivalenol (DON) determination. A total of 328 polymorphic microsatellite loci were used to construct a genetic linkage map in this population and together these data were used to identify QTL controlling FHB resistance, accumulation of DON, and agronomic and spike morphology traits. The analysis identified QTL for different types of FHB resistance in four intervals on chromosomes 2DL, 3BS, and 4B. The QTLs on 4B and 3BS proximal to the centromere are novel and not reported elsewhere. QTL controlling accumulation of DON independent of FHB resistance were located on chromosomes 2DS and 5AS. Lines carrying FHB resistance alleles on 2DL and 3BS showed a 32% decrease in disease spread after single-floret injection. Lines carrying FHB resistance alleles on 3BS and 4B showed a 27% decrease from the mean in field infection. Finally, lines carrying favourable alleles on 3BS and 5AS, showed a 17% reduction in DON accumulation. The results support a polygenic and quantitative mode of inheritance and report novel FHB resistance loci. The data also suggest that resistance to FHB infection and DON accumulation may be controlled, in part, by independent loci and (or) genes.
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".