High density genetic mapping of Fusarium head blight resistance QTL in tetraploid wheat
Bibliographic record
Abstract
Breeding for Fusarium head blight (FHB) resistance in durum wheat is complicated by the quantitative trait expression and narrow genetic diversity of available resources. High-density mapping of the FHB resistance quantitative trait loci (QTL), evaluation of their co-localization with plant height and maturity QTL and the interaction among the identified QTL are the objectives of this study. Two doubled haploid (DH) populations, one developed from crosses between Triticum turgidum ssp. durum lines DT707 and DT696 and the other between T. turgidum ssp. durum cv. Strongfield and T. turgidum ssp. carthlicum cv. Blackbird were genotyped using the 90K Infinium iSelect chip and evaluated phenotypically at multiple field FHB nurseries over years. A moderate broad-sense heritability indicated a genotype-by-environment interaction for the expression of FHB resistance in both populations. Resistance QTL were identified for the DT707 × DT696 population on chromosomes 1B, 2B, 5A (two loci) and 7A and for the Strongfield × Blackbird population on chromosomes 1A, 2A, 2B, 3A, 6A, 6B and 7B with the QTL on chromosome 1A and those on chromosome 5A being more consistently expressed over environments. FHB resistance co-located with plant height and maturity QTL on chromosome 5A and with a maturity QTL on chromosome 7A for the DT707 × DT696 population. Resistance also co-located with plant height QTL on chromosomes 2A and 3A and with maturity QTL on chromosomes 1A and 7B for the Strongfield × Blackbird population. Additive × additive interactions were identified, for example between the two FHB resistance QTL on chromosome 5A for the DT707 × DT696 population and the FHB resistance QTL on chromosomes 1A and 7B for the Strongfield × Blackbird population. Application of the Single Nucleotide Polymorphic (SNP) markers associated with FHB resistance QTL identified in this study will accelerate combining genes from the two populations.
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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 | 0.001 | 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".