Genome‐wide transcriptomic analyses provide insights into the lifestyle transition and effector repertoire of <i>Leptosphaeria maculans</i> during the colonization of <i>Brassica napus</i> seedlings
Bibliographic record
Abstract
Molecular interaction between the causal agent of blackleg disease, Leptosphaeria maculans (Lm), and its host, Brassica napus, is largely unknown. We applied a deep RNA-sequencing approach to gain insight into the pathogenicity mechanisms of Lm and the defence response of B. napus. RNA from the infected susceptible B. napus cultivar Topas DH16516, sampled at 2-day intervals (0-8 days), was sequenced and used for gene expression profiling. Patterns of gene expression regulation in B. napus showed multifaceted defence responses evident by the differential expression of genes encoding the pattern recognition receptor CERK1 (chitin elicitor receptor kinase 1), receptor like proteins and WRKY transcription factors. The up-regulation of genes related to salicylic acid and jasmonic acid at the initial and late stages of infection, respectively, provided evidence for the biotrophic and necrotrophic life stages of Lm during the infection of B. napus cotyledons. Lm transition from biotrophy to necrotropy was also supported by the expression function of Lm necrosis and ethylene-inducing (Nep-1)-like peptide. Genes encoding polyketide synthases and non-ribosomal peptide synthetases, with potential roles in pathogenicity, were up-regulated at 6-8 days after inoculation. Among other plant defence-related genes differentially regulated in response to Lm infection were genes involved in the reinforcement of the cell wall and the production of glucosinolates. Dual RNA-sequencing allowed us to define the Lm candidate effectors expressed during the infection of B. napus. Several candidate effectors suppressed Bax-induced cell death when transiently expressed in Nicotiana benthamaina leaves.
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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 | 0.000 | 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) | 0.001 | 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".