Deciphering common temporal transcriptional response during powdery mildew disease in plants using meta-analysis

Abstract

Abstract Powdery mildew caused by the different fungal species of the order Erysiphales, is one of the deadliest plant disease causing havoc production loss of major crops such as wheat, barley, grape, tomato and other economically important plants. Plants response to powdery mildew infection, the spatiotemporal dynamics of the molecular cascades and the role of defense phytohormone signaling events are still at grave. In the current study, we have used a meta-analysis approach to integrate 5 different microarray datasets by adjusting the batch effect. This integrated dataset was further used for downstream analysis, such as differential expression and pathway analysis. A large set of 5350 genes showed elevated expression upon infection in Arabidopsis thaliana. These genes majorly comprised of transcriptional regulators, phytohormone signaling pathways and secondary metabolic pathways. Furthermore, to study the shared and species-specific core gene sets involved in whole plant adaptation during powdery mildew infection, we extended our study in wheat and barley from monocots and grape from dicots. A core gene set of 184 key powdery mildew responsive genes were reported in the meta-analysis majorly from the lignin biosynthesis, circadian rhythm and hormone responsive pathways. 390 transcription factors (TFs) in Arabidopsis were further identified to differentially express at any one time point that were classified in 10 clusters based on their expression pattern. Finally, with co-expression analysis, we identified powdery mildew response network consisting of 1601 genes and 30,781 interactions. Subnetwork analysis revealed WRKY70 as potential hub that co-expressed with other WRKY transcription factors and phytohormone signaling pathway genes. Thus, the overlapping differentially expressed genes reported here would serve as useful resource for subsequent research and as a potential set of molecular biomarkers for powdery mildew disease in plants.