Integration of meta-QTL discovery with omics: Towards a molecular breeding platform for improving wheat resistance to Fusarium head blight
Why this work is in the frame
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Bibliographic record
Abstract
Fusarium head blight (FHB) is a global wheat disease that devastates wheat production. Resistance to FHB spread within a wheat spike (type II resistance) and to mycotoxin accumulation in infected kernel (type III resistance) are the two main types of resistance. Of hundreds of QTL that have been reported, only a few can be used in wheat breeding because most show minor and/or inconsistent effects in different genetic backgrounds. We describe a new strategy for identifying robust and reliable meta-QTL (mQTL) that can be used for improvement of wheat FHB resistance. It involves integration of mQTL analysis with mQTL physical mapping and identification of single-copy markers and candidate genes. Using meta-analysis, we consolidated 625 original QTL from 113 publications into 118 genetic map-based mQTL (gmQTL). These gmQTL were further located on the Chinese Spring reference sequence map. Finally, 77 high-confidence mQTL (hcmQTL) were selected from the reference sequence-based mQTL (smQTL). Locus-specific single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers and 17 genes responsive to FHB were then identified in the hcmQTL intervals by combined analysis of transcriptomic and proteomic data. This work may lead to a comprehensive molecular breeding platform for improving wheat resistance to FHB.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it