Genetic architecture of disease resistance and tolerance in Douglas-fir trees
Bibliographic record
Abstract
Abstract Understanding the genetic architecture of tolerance and resistance to pathogens is important to monitor and maintain resilient tree populations. Here we investigate the genetic basis of tolerance and resistance to needle cast disease in Douglas-fir (Pseudotsuga menziesii) caused by two fungal pathogens: Swiss needle cast (SNC) caused by Nothophaeocryptopus gaeumannii, and Rhabdocline needle cast (RNC) caused by Rhabdocline pseudotsugae). We performed a case-control genome-wide association analysis (GWA) and found these traits to be polygenic and under selection. We showed that stomatal regulation as well as ethylene and jasmonic acid pathways are important for resisting SNC infection and secondary metabolite pathways play a role in tolerating SNC once the plant is infected. We identified a key upstream transcription factor of plant defence, ERF1, as the main candidate for RNC resistance. Our findings contribute to the understanding of the highly polygenic architectures underlying disease resistance and tolerance in Douglas-fir and have important implications for forestry and conservation as the climate changes.
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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".