Gene Expression Profiling Analysis of Resistant and Susceptible Tea Cultivars in Response to Tea Blister Blight (<i>Exobosidium vexans</i> Massee)
Bibliographic record
Abstract
The resistant and susceptible tea cultivars were selected for revealing the defense response mechanism induced by tea blister blight. The DEGs before and after infection by tea blister blight were analyzed based on RNA sequencing and digital expression spectrum. The results showed a total of 974 DEGs were identified, of which 122 DEGs were co-expressed genes in both resistant and susceptible cultivars, 364 DEGs were specific genes only in blister disease-resistant cultivar, and 488 DEGs were specific genes only in blight disease-susceptible cultivar. The infection of tea blister blight mainly affected the expression levels of key genes involved in metabolic pathways, protein processing in endoplasmic reticulum, biosynthesis of secondary metabolites, plant-pathogen interaction, plant hormone signal transduction, starch and sucrose metabolism, phenylalanine, tyrosine and tryptophan biosynthesis and so on. These DEGs included disease resistance protein gene, hydrolase gene, cell wall reinforcement genes, transcription factor genes, plant hormones and their signal transduction genes, secondary metabolism and oxidase genes, transporter gene and so on. The differential expressions of 6 genes were verified by Real-time quantitative PCR, which showed a general consistency consistent with the results of transcriptome sequencing. This study preliminarily clarified the influence of tea blister blight infection on gene transcription levels in tea plants with this study, which laid a theoretical foundation for researching the molecular mechanism of disease resistance in tea plants.
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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) | 0.001 | 0.001 |
| 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) | 0.001 | 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".