Transcriptomic characterization of the B. napus – L. maculans pathosystem
Bibliographic record
Abstract
Canola (Brassica napus L.) is one of the world’s most valuable oilseed crops and sustains a multibillion-dollar industry. Currently, blackleg disease caused by the hemibiotrophic fungus L. maculans threatens the canola industry in Canada, Europe, and Australia and causes over $500 Million in crop loss per annum. Disease control relies heavily on crop resistance mediated by SOBIR1-interacting receptor-like proteins, such as Rlm2 and LepR1. Understanding the downstream plant immune responses activated by SOBIR1-RLP complexes is currently an area of interest in plant pathology. This work profiles the transcriptome of canola cotyledons from the initial stages of infection through to the necrotrophic stage of disease, in both compatible and incompatible (Rlm2, LepR1) interactions. A spatial dimension was added to this dataset through the application of laser microdissection and captured early signaling events during initial host colonization. Through transcriptomic interrogation I identified plant immune responses associated with resistance, such as jasmonic acid signaling, lignin and callose production, and calcium signaling. Additionally, I designed the program SeqEnrich to build regulatory networks and predict transcriptional control of these important immune processes. SeqEnrich has been made publicly available and will serve as a valuable resource to researchers studying transcriptional control of biological processes in B. napus and Arabidopsis. Further, sequencing data was functionally validated with mutant screens, microscopy, measurement of endogenous jasmonic acid concentrations, and physiological experiments with calcium channel blockers. This identified positive regulators of plant resistance, including uncharacterized receptor-like proteins, that are the focus of ongoing research. To my knowledge, this is the first study to apply LMD and RNA-Seq in combination to characterize early signaling events during a plant host-microbe interaction, and the first transcriptomic investigation into LepR1- and Rlm2-mediated immunity. Together, this information will be valuable to researchers studying blackleg disease, regulation of transcription in plants, and plant host pathogen interactions in general.
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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 | 0.001 |
| 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) | 0.001 | 0.001 |
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".