Study on Innate Immunity of Cotton to Biological Stress Based on Transcriptome Analysis
Bibliographic record
Abstract
Cotton ( Gossypium spp.), as an important economic crop in the world, is often affected by biotic stresses such as pathogenic fungi, bacteria and pests, resulting in reduced yield and quality. Exploring its natural immune response mechanism is of great significance for improving disease and insect resistance and ensuring agricultural production safety. Based on transcriptome data, this study systematically analyzed the changes in gene expression of cotton when it was subjected to biotic stress, screened out key genes and signaling pathways closely related to defense response, including pathogen-related proteins (PRs), defensins, hormone regulatory factors, etc., and deeply explored the transcriptional regulatory mechanisms of two types of immune responses, PTI (PAMP-triggered immunity) and ETI (effector-triggered immunity). The relevant immune regulatory network was further constructed, and several resistance candidate genes with application potential were screened. This study provides a molecular basis for a deeper understanding of the natural immune mechanism of cotton, and provides theoretical references and gene resources for the breeding of highly resistant cotton varieties, hoping to promote the development of green prevention and control of cotton pests and diseases and molecular breeding.
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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".