Integrated Omics Reveal Coordinated Defense Networks in Annona squamosa Against Fusarium acutatum Infection
Bibliographic record
Abstract
Root rot disease severely threatens tropical fruit production, leading to plant mortality and reduced yields; however, the mechanisms of host defense responses and pathogen infection remain poorly understood. In this study, Fusarium acutatum was isolated from diseased Annona squamosa roots and identified through morphological features and ITS phylogeny (99.8% identity). Infection triggered a marked activation of antioxidant defenses, with elevated POD, SOD, PAL, PPO, and CAT activities. Transcriptomic and TMT-based quantitative proteomic analyses identified 23,791 and 74,403 differentially expressed genes (DEGs) and 367 and 609 differentially expressed proteins (DEPs) in root at 5 and 10 days post inoculation, respectively, relative to the control. These DEGs and DEPs were consistently enriched in pathways involving redox regulation, protein synthesis and processing, ubiquitin-mediated proteolysis, phenylpropanoid and flavonoid metabolism, cell wall remodeling, plant–pathogen interaction and MAPK signaling. Integrated transcriptomic–proteomic correlation analysis showed clear positive associations between key defense-related genes and proteins, suggesting that phenylpropanoid metabolism and reactive oxygen species (ROS) scavenging play central roles in resistance. Key genes such as CHI2, CHS, and CYP were strongly induced and validated by qPCR, supporting coordinated activation of the defense systems. Furthermore, F. acutatum exhibited upregulation of 50 pathogenic-related proteins, including 4 cell wall-degrading enzymes (e.g., CBH1, pectate lyase), 5 metabolic regulation or signal transduction enzymes (e.g., gabD, TPI, and ENO) and 3 potential effectors, suggesting coordinated pathogen strategies for host colonization. Collectively, this study provides comprehensive multi-omics insight into the molecular mechanisms underlying A. squamosa defense against F. acutatum and offers candidate targets supported by omics evidence, serving as a theoretical reference for the management of root rot.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".