Molecular mapping of QTLs for resistance to<i>Gibberella</i>ear rot, in corn, caused by<i>Fusarium graminearum</i>
Bibliographic record
Abstract
Gibberella ear rot, caused by the fungus Fusarium graminearum Schwabe, is a serious disease of corn (Zea mays) grown in northern climates. Infected corn is lower yielding and contains toxins that are dangerous to livestock and humans. Resistance to ear rot in corn is quantitative, specific to the mode of fungal entry (silk channels or kernel wounds), and highly influenced by the environment. Evaluations of ear rot resistance are complex and subjective; and they need to be repeated over several years. All of these factors have hampered attempts to develop F. graminearum resistant corn varieties. The aim of this study was to identify molecular markers linked to the genes for resistance to Gibberella ear rot. A recombinant inbred (RI) population, produced from a cross between a Gibberella ear rot resistant line (CO387) and a susceptible line (CG62), was field-inoculated and scored for Gibberella ear rot symptoms in the F4, F6, and F7 generations. The distributions of disease scores were continuous, indicating that resistance is probably conditioned by multiple loci. A molecular linkage map, based on segregation in the F5 RI population, contained 162 markers distributed over 10 linkage groups and had a total length of 2237 cM with an average distance between markers of 13.8 cM. Composite interval mapping identified 11 quantitative trait loci (QTLs) for Gibberella ear rot resistance following silk inoculation and 18 QTLs following kernel inoculation in 4 environments that accounted for 6.7%-35% of the total phenotypic variation. Only 2 QTLs (on linkage group 7) were detected in more than 1 test for silk resistance, and only 1 QTL (on linkage group 5) was detected in more than 1 test for kernel resistance, confirming the strong influence of the environment on these traits. The majority of the favorable alleles were derived from the resistant parent (CO387). The germplasm and markers for QTLs with significant phenotypic effects may be useful for marker-assisted selection to incorporate Gibberella ear rot resistance into commercial corn cultivars.
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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 | 0.000 |
| 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".