Genome‐wide association analysis of winter survival in a diverse Canadian winter wheat population
Bibliographic record
Abstract
Vrn-A1 (VERNALIZATION A1) and Fr-A2 (FROST RESISTANCE A2) have been associated with variation in winter survival of wheat (Triticum aestivum L.). The beneficial alleles of Vrn-A1 and Fr-A2 are largely fixed in Canadian winter wheat germplasm, rendering the associated molecular markers ineffective for marker-assisted selection (MAS) in elite populations. The objectives were to (i) identify quantitative trait loci (QTLs) for winter survival in eastern Canada and determine their usefulness for MAS and (ii) explore the underlying genetic mechanisms of superior winter survival in the region. A subpopulation (n = 321) of the Canadian Winter Wheat Diversity Panel, consisting of genotypes that were fixed for the beneficial alleles of vrn-A1 and Fr-A2, was previously evaluated for winter survival in three eastern Canadian environments (Elora 2016-2017, CÉROM 2017-2018, and Elora 2017-2018). Genome-wide association mapping identified three significant QTLs for winter survival, a previously identified QTL on chromosome 5A, and two novel QTLs on chromosomes 5D and 7B. These QTLs were of low-to-moderate marker utility (0.1473-0.4796) and conferred a 0.7%-1.8% increase in mean winter survival. In silico analyses revealed that an array of biotic and abiotic stress responses are implicated in winter survival in eastern Canada, which challenges the notion that lethal temperature is the primary cause of winterkill in some regions. As significant winterkill events are sporadic in the region, it may be beneficial to identify individual components of winter survival that can be examined in artificial environments.
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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 | 0.001 |
| 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".