Association Analysis Identifies Melampsora ×columbiana Poplar Leaf Rust Resistance SNPs
Bibliographic record
Abstract
Populus species are currently being domesticated through intensive time- and resource-dependent programs for utilization in phytoremediation, wood and paper products, and conversion to biofuels. Poplar leaf rust disease can greatly reduce wood volume. Genetic resistance is effective in reducing economic losses but major resistance loci have been race-specific and can be readily defeated by the pathogen. Developing durable disease resistance requires the identification of non-race-specific loci. In the presented study, area under the disease progress curve was calculated from natural infection of Melampsora ×columbiana in three consecutive years. Association analysis was performed using 412 P. trichocarpa clones genotyped with 29,355 SNPs covering 3,543 genes. We found 40 SNPs within 26 unique genes significantly associated (permutated P<0.05) with poplar rust severity. Moreover, two SNPs were repeated in all three years suggesting non-race-specificity and three additional SNPs were differentially expressed in other poplar rust interactions. These five SNPs were found in genes that have orthologs in Arabidopsis with functionality in pathogen induced transcriptome reprogramming, Ca²⁺/calmodulin and salicylic acid signaling, and tolerance to reactive oxygen species. The additive effect of non-R gene functional variants may constitute high levels of durable poplar leaf rust resistance. Therefore, these findings are of significance for speeding the genetic improvement of this long-lived, economically important organism.
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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) | 0.004 | 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".