Comparative Transcriptome Analysis of Rutabaga (Brassica napus) Cultivars Indicates Activation of Salicylic Acid and Ethylene-Mediated Defenses in Response to Plasmodiophora brassicae
Bibliographic record
Abstract
Clubroot, caused by Plasmodiophora brassicae Woronin, is an important soilborne disease of Brassica napus L. and other crucifers. To improve understanding of the mechanisms of resistance and pathogenesis in the clubroot pathosystem, the rutabaga (B. napus subsp. rapifera Metzg) cultivars ‘Wilhelmsburger’ (resistant) and ‘Laurentian’ (susceptible) were inoculated with P. brassicae pathotype 3A and their transcriptomes were analyzed at 7, 14, and 21 days after inoculation (dai) by RNA sequencing (RNA-seq). Thousands of transcripts with significant changes in expression were identified in each host at each time-point in inoculated vs. non-inoculated plants. Molecular responses at 7 and 14 dai supported clear differences in the clubroot response mechanisms of the two genotypes. Both the resistant and the susceptible cultivars activated receptor-like protein (RLP) genes, resistance (R) genes, and genes involved in salicylic acid (SA) signaling as clubroot defense mechanisms. In addition, genes related to calcium signaling and genes encoding leucine-rich repeat (LRR) receptor kinases, the respiratory burst oxidase homolog (RBOH) protein, and transcription factors such as WRKYs, ethylene responsive factors, and basic leucine zippers (bZIPs), appeared to be upregulated in ‘Wilhelmsburger’ to restrict P. brassicae development. Some of these genes are essential components of molecular defenses, including ethylene (ET) signaling and the oxidative burst. Our study highlights the importance of activation of genes associated with SA- and ET-mediated responses in the resistant cultivar. A set of candidate genes showing contrasting patterns of expression between the resistant and susceptible cultivars was identified and includes potential targets for further study and validation through approaches such as gene editing.
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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".