Transcriptome-based identification of genes related to resistance against <i>Botrytis elliptica</i> in <i>Lilium regale</i>
Bibliographic record
Abstract
A major production constraint of lilies is gray mold caused by the necrotrophic fungus Botrytis elliptica. The molecular basis of lily plant resistance to B. elliptica remains largely unexplored. To systematically dissect transcriptomic responses, we constructed four RNA-seq libraries from the leaves of Lilium regale, a promising Chinese wild Lilium species, after B. elliptica infection for 0, 4, 12, or 24 h. The sequence reads were assembled into 96 416 unigenes, of which 7697 were differentially expressed. Profiling analysis revealed changes in gene expression, including 2261 downregulated genes and 3599 upregulated genes. Quantitative real-time polymerase chain reaction analysis of 39 defense-related unigenes confirmed that the transcriptional changes of these genes presented in the RNA-seq data were predominately affected by B. elliptica infection. Key B. elliptica modulated genes played roles in defense responses mediated by phytohormones involved in jasmonate signaling, whereas salicylic acid and ethylene were not involved. Among transcription factors, some WRKYs, MYB, and ethylene responsive factor were clearly upregulated. Additionally, a group of genes encoding known important defense-related proteins, such as receptor-like kinases, antioxidant enzymes, polyphenol oxidase, pathogenesis-related proteins, and proteins associated with phenylpropanoid metabolism, exhibited high transcript abundances. Furthermore, the expressions of selected candidate genes were induced more rapidly and strongly in the resistant genotype than in the susceptible genotype. Taken together, the results provide a better understanding of the defense responses involved in the crosstalk between the lily and B. elliptica and a valuable set of sequence data for gray mold resistant candidate gene discovery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 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".