Uncovering novel genetic variation in Aegilops tauschii the wheat D genome progenitor
Bibliographic record
Abstract
Wheat is one of the world’s most important staple crops, accounting for roughly 20% of all calories consumed globally. However, wheat production faces multiple significant challenges that may limit yields, especially in the face of a changing climate. One of these major challenges is the threat posed by different pests and pathogens. To combat these threats and safeguard wheat yields, identifying novel sources of disease resistance represents an important objective in wheat breeding. Wheat wild relatives, such as Aegilops tauschii, the wheat D genome progenitor, contain valuable genetic diversity that can be harnessed to achieve this goal. In this study, a diversity panel of Ae. tauschii accessions collected from across the species endemic range was assessed for resistance against two important diseases of wheat: stripe rust and eyespot. This enabled a k-mer based association mapping approach to rapidly identify novel genetic associations linked to resistance against both diseases. In collaboration with researchers in North America, and a European wheat breeder, RAGT Seeds Ltd, multiple unique isolates of Puccinia striiformis f. sp. tritici (PST) the causative agent of stripe rust, were phenotyped against the two major lineages of Ae. tauschii. This led to the discovery of several new alleles of a major broad-spectrum R gene, Yr28, in addition to the identification of two isolate specific R genes on chromosomes 5DL and 2DS, that convey protection against a Canadian race, and a UK race of PST respectively. Furthermore, employing the same methodology to cereal eyespot, a disease with sparsely documented resistance available, led to the discovery of the first major R gene for this disease in many years. This gene, designated Pch4, provides potent resistance comparable to that of the most commonly deployed R gene Pch1, and was demonstrated here to convey resistance in both Ae. tauschii and hexaploidy wheat. The research contained within this study represents a significant step forward in our understanding of the novel genetic resistance available in Ae. tauschii for both diseases and will aid in future research to uncover further genetic loci relevant for wheat breeding.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".