Bioscience Methods 2024, Vol.15, No.3, 102-113 http://bioscipublisher.com/index.php/bm 109 essential for a holistic understanding of rice-pathogen interactions but presents several challenges. Proteomics, for instance, provides insights into protein-level changes during rice-microbe interactions, which are crucial for understanding disease resistance mechanisms (Figure 2) (Wei et al., 2023). However, combining these data sets requires sophisticated analytical tools and methodologies that can handle the complexity and volume of multi-omics data (Chulang et al., 2010). The integration of epigenomic data, such as miRNA and siRNA regulation, further complicates the analysis but is necessary for a complete picture of host-pathogen interactions (Sarki et al., 2020). Figure 2 Proteomics-based schematic diagram of rice–microbe interactions (Adopted from Wei et al., 2023) Image caption: Sensing of bacterial and fungal pathogens by membrane-localized pattern recognition receptors leads to the phosphorylation of MAPK cascade and CDPKs in rice, which subsequently activates the downstream transcription factors, especially WRKKYs. The abundance of glycoside hydrolase family proteins (GHs), reactive-oxygen-species-related proteins (ROSs), pathogenesis-related proteins (PRs), cell-wall-modification-related proteins, and protein-degradation-related proteins are significantly increased and highly accumulated in the apoplastic region through protein secretion. Secondary metabolite biosynthesis-related proteins are also highly accumulated upon bacterial (left panel) and fungal pathogen (right panel) infection. Accumulation of SA and ET biosynthesis regulating proteins prohibitin, ICS1, and HSM were increased upon bacterial and pathogen infection, respectively. Phosphorylation of PP2Cs, a negative regulator of ABA signaling, is increased upon bacterial infection (Adopted from Wei et al., 2023) 7 Future Directions 7.1 Advancements in transcriptomics and emerging technologies The field of transcriptomics has seen significant advancements with the advent of next-generation sequencing technologies, particularly RNA sequencing (RNA-seq). These technologies have enabled comprehensive profiling of gene expression, providing deeper insights into the molecular mechanisms underlying host-pathogen interactions in rice. Emerging technologies such as dual RNA-seq, CRISPR/Cas9 screening, and organ-on-chip models are poised to further revolutionize the study of these interactions. Dual RNA-seq, for instance, allows simultaneous analysis of gene expression changes in both the pathogen and the host, offering a more holistic view of the interaction dynamics (Westermann et al., 2012; Baddal, 2019). Additionally, the development of high-quality transcriptomes using microdissection-based RNA sequencing approaches has improved our understanding of specific pathogen-host interactions, such as those between Magnaporthe oryzae and Oryza sativa (Jeon et al., 2010).
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