Integrated genome and transcriptome analysis reveals pathogenic mechanisms of Calonectria eucalypti in Eucalyptus leaf blight
- Author: mycolabadmin
- 7/27/2025
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Summary
Scientists studied a dangerous fungus called Calonectria eucalypti that kills eucalyptus trees worldwide. They sequenced the fungus’s entire genetic code and tracked which genes it turned on during infection. They found that the fungus uses different strategies at different stages of infection, starting with penetration, then breaking down plant cell walls, and finally stealing nutrients. This research helps us understand how the fungus works and develop better ways to protect eucalyptus plantations.
Background
Calonectria eucalypti is a destructive fungal pathogen causing Eucalyptus leaf blight in China and Indonesia, affecting millions of hectares of plantations globally. Despite its significant ecological and economic impact, the molecular mechanisms underlying its pathogenicity remain largely unexplored.
Objective
This study aimed to elucidate the pathogenic mechanisms of C. eucalypti through integrated genome and transcriptome analyses, focusing on identifying virulence-related genes and their expression patterns during infection.
Results
The 62.1 Mb genome contained 13,112 predicted genes including 1,006 carbohydrate-active enzymes, 351 candidate effectors, and 90 secondary metabolite biosynthetic gene clusters. Transcriptome analysis identified stage-specific expression patterns of pathogenicity-related genes, with glycoside hydrolases showing the strongest induction during infection stages.
Conclusion
This study provides the first integrated genome and infection-stage transcriptome map of C. eucalypti, revealing coordinated, stage-specific deployment of pathogenicity-related genes. The findings establish a foundational resource for understanding fungal virulence mechanisms and developing targeted disease management strategies for Eucalyptus leaf blight.
- Published in:BMC Genomics,
- Study Type:Genomic and Transcriptomic Analysis,
- Source: PMC12302842, PMID: 40717072