Exploring Mechanisms of Quantitative Resistance to Leptosphaeria maculans (Blackleg) in the Cotyledons of Canola (Brassica napus) Based on Transcriptomic and Microscopic Analyses
Bibliographic record
Abstract
Using resistant cultivars is a common approach to managing blackleg of canola/rapeseed caused by Leptosphaeria maculans (Lm). Quantitative resistance (QR), as opposed to major-gene resistance, is of interest because it is generally more durable, due to its multi-genetic basis. However, the mechanisms and genes underlying QR are mostly unknown. In this study, potential QR modes of action in “74-44 BL” was explored. This Canadian canola cultivar showed moderate but consistent race-nonspecific resistance at the cotyledon and adult-plant stages. A susceptible cultivar, “Westar”, was used as a control. After inoculation, the lesions developed more slowly on the cotyledons of 74-44 BL than those of Westar. We used RNA sequencing (-RNA-seq) to identify genes and their functions, putatively related to this resistance, and found that genes involved in programmed cell death (PCD), reactive oxygen species (ROS), signal transduction or intracellular endomembrane transport were most differentially expressed. ROS production was assessed in relation to Lm hyphal growth and lesion size; it occurred beyond the tissue colonized by Lm in 74-44 BL and appeared to trigger rapid cell death, limiting cotyledon colonization by Lm. In contrast, Lm grew more rapidly in Westar, often catching up with the ring of ROS and surpassing lesion boundaries. It appears that QR in 74-44 BL cotyledons is associated with limited colonization by Lm possibly mediated via ROS. The RNA-seq data also showed a link between ROS, signal transduction, and endomembrane vesicle trafficking, as well as PCD in the resistance. These results provide a starting point for a better understanding of the mechanisms behind QR against Lm in canola.
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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".