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Genome sequencing and analysis of isolates of Cytospora sorbicola and Cytospora plurivora associated with almond and peach canker

Summary

Scientists have sequenced the complete genetic code of two fungal species that cause destructive canker diseases in almond and peach trees. These fungi are difficult to control once they infect trees, and developing disease-resistant plant varieties is the best approach to protect orchards. The genetic information from this study will help researchers understand how these fungi cause disease and develop better strategies to breed resistant fruit trees.

Background

Cytospora sorbicola and C. plurivora are significant canker pathogens affecting stone fruits and woody plants, severely limiting orchard productivity and longevity. These pathogens are challenging to control with no cure once established. Understanding plant-pathogen interactions is essential for developing resistant plant varieties.

Objective

To present genome sequencing and analysis of two isolates each of C. sorbicola and C. plurivora to facilitate understanding of plant-pathogen interactions. The study aimed to identify putative virulence determinants and conduct phylogenomic analysis to clarify the taxonomic status of related Cytospora species.

Results

C. plurivora genomes assembled to 38.4 ± 0.275 Mbp with 9,878 ± 17.5 protein-coding genes, while C. sorbicola genomes assembled to 40.48 ± 0.11 Mbp with 10,161 ± 34.5 genes. Phylogenomic analysis based on conserved single-copy genes strongly suggests C. paraplurivora is a subspecies of C. plurivora with 98-99% average amino acid identity.

Conclusion

High-quality genome assemblies for C. sorbicola and C. plurivora isolates are presented as critical resources for future plant-pathogen interaction studies. The authors recommend amending the classification of C. paraplurivora sp. nov. to C. plurivora based on phylogenomic evidence. These genome resources will support expression profiling, knockout mutation studies, and genetic diversity research.
  • Published in:PLoS One,
  • Study Type:Genomic Analysis,
  • Source: PMID: 41105662, DOI: 10.1371/journal.pone.0334178
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