Sclerotinia sclerotiorum is a devastating necrotrophic pathogen causing significant yield losses in oilseed Brassica crops worldwide. Understanding pathogen virulence mechanisms and host–pathogen interactions is essential for identifying key molecular determinants underlying disease response. In this study, we performed an integrative meta-analysis of five publicly available RNA-seq datasets, including three host and two pathogen transcriptomic datasets, to investigate molecular responses and effector candidates associated with S. sclerotiorum infection. Effector prediction analysis identified 1110 up-regulated and 1114 down-regulated differentially expressed effector candidates in the two pathogen datasets. Of these, 17 were identified as core effector candidates in each pathogen dataset, representing potential molecular signatures associated with host infection. Functional enrichment analysis revealed that these candidate effectors were associated with infection-related processes, including cell wall degradation, oxidative stress response, metabolic regulation, and signal transduction. Furthermore, we developed BScPDb, a user-friendly database containing curated information on host differentially expressed genes and pathogen effector candidates. This study provides a comprehensive molecular resource for understanding the S. sclerotiorum -Brassica interaction and prioritizing candidate genes and effectors for future functional validation and utilization.
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Budhlakoti et al. (2026) studied this question.
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