| Sumario: | Cassava (Manihot esculenta Crantz) is a staple crop for millions of people worldwide, particularly in tropical and subtropical regions, where its productivity is increasingly threatened by a range of emerging and re-emerging pathogens. Viral, bacterial, and fungal diseases affecting cassava have caused substantial yield losses and pose serious risks to food security and rural livelihoods. In this context, comprehensive genomic characterization of priority cassava pathogens has become an essential tool for understanding pathogen diversity, evolution, and spread.
Genome profiling enables high-resolution identification of pathogen lineages, detection of genetic variation associated with virulence or adaptation, and improved development of molecular diagnostics. When combined with geographical distribution data, genomic information provides critical insights into the spatial dynamics of cassava diseases, revealing patterns of emergence, dissemination routes, and regional hotspots of infection. Such integrated approaches support more accurate risk assessment and inform targeted surveillance and management strategies.
In parallel, the compilation and curation of official disease reports into standardized, accessible datasets are vital for ensuring data reliability and traceability. In this study, curated genomic and epidemiological data were integrated and visualized using the PestDisplace platform (PestDisPlace - Home), enabling the spatial mapping of pathogen genome profiles alongside official disease reports. This approach allows for the validation of genomic findings within an epidemiological framework and facilitates comparisons across regions and time. Together, genome profiling, geographical mapping, curated reporting, and the use of PestDisplace form a robust foundation for strengthening cassava disease monitoring, supporting early warning systems, and guiding evidence-based interventions to protect this globally important crop.
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