Comparative transcriptome profiling and weighted gene co-expression network analysis to identify core genes in maize (Zea mays L.) silks infected by multiple fungi

Comparative transcriptome profiling and co-expression network analysis uncover the key genes associated with pear petal defense responses against Monilinia laxa infection

Pear brown rot and blossom blight caused by Monilinia laxa seriously affect pear production worldwide. Here, we compared the transcriptomic profiles of petals after inoculation with M. laxa using two pear cultivars with different levels of sensitivity to disease (Sissy, a relatively tolerant cultivar, and Kristalli, a highly susceptible cultivar). Physiological indexes were also monitored in the petals of both cultivars at 2 h and 48 h after infection (2 HAI and 48 HAI). RNA-seq data and weighted gene co-expression network analysis (WGCNA) allowed the identification of key genes and pathways involved in immune- and defense-related responses that were specific for each cultivar in a time-dependent manner. In particular, in the Kristalli cultivar, a significant transcriptome reprogramming occurred early at 2 HAI and was accompanied either by suppression of key differentially expressed genes (DEGs) involved in the modulation of any defense responses or by activation of DEGs acting as sensitivity factors promoting susceptibility. In contrast to the considerably high number of DEGs induced early in the Kristalli cultivar, upregulation of specific DEGs involved in pathogen perception and signal transduction, biosynthesis of secondary and primary metabolism, and other defense-related responses was delayed in the Sissy cultivar, occurring at 48 HAI. The WGCNA highlighted one module that was significantly and highly correlated to the relatively tolerant cultivar. Six hub genes were identified within this module, including three WRKY transcription factor-encoding genes: WRKY 65 (pycom05g27470), WRKY 71 (pycom10g22220), and WRKY28 (pycom17g13130), which may play a crucial role in enhancing the tolerance of pear petals to M. laxa. Our results will provide insights into the interplay of the molecular mechanisms underlying immune responses of petals at the pear-M. laxa pathosystem.

S. A, Raveendran AP, Chaudhary A, Shanmugam A, Arunachalam A. Comparative transcriptomic and weighted gene co-expression network analysis to identify the core genes in the cultivars of Musa acuminata under both infected and chemical perturbated conditions

Banana is a high nutrient crop, which ranks fourth in terms of gross value production. Fusarium wilt of banana, caused by Fusarium oxysporum f. sp. cubense tropical race 4 (FocTR4), is considered the most destructive disease leading to the complete loss of production of the Cavendish cultivars Berangan, Brazilian and Williams, which are vulnerable to the infection of FocTR4. However, the treatment with benzothiadiazole, a synthetic salicylic analog, is aimed to induce resistance in plants. Thus, the treatments pertaining to the banana plants subjected to the Foc infection within the chosen cultivars were compared with chemically treated samples obtained at different time intervals for a short duration (0-4 days). The integrated omics analyses considering the parameters of WGCNA, functional annotation, and protein-protein interactions revealed that many pathways have been negatively influenced in Cavendish bananas under FocTR4 infections and the number of genes influenced also increased over time in Williams cultivar. Furthermore, elevation in immune response and resistance genes were also observed in the roots of the Cavendish banana.

Network Analysis of Publicly Available RNA-seq Provides Insights into the Molecular Mechanisms of Plant Defense against Multiple Fungal Pathogens in Arabidopsis thaliana

Fungal pathogens can have devastating effects on global crop production, leading to annual economic losses ranging from 10% to 23%. In light of climate change-related challenges, researchers anticipate an increase in fungal infections as a result of shifting environmental conditions. However, plants have developed intricate molecular mechanisms for effective defense against fungal attacks. Understanding these mechanisms is essential to the development of new strategies for protecting crops from multiple fungi threats. Public omics databases provide valuable resources for research on plant-pathogen interactions; however, integrating data from different studies can be challenging due to experimental variation. In this study, we aimed to identify the core genes that defend against the pathogenic fungi Colletotrichum higginsianum and Botrytis cinerea in Arabidopsis thaliana. Using a custom framework to control batch effects and construct Gene Co-expression Networks in publicly available RNA-seq dataset from infected A. thaliana plants, we successfully identified a gene module that was responsive to both pathogens. We also performed gene annotation to reveal the roles of previously unknown protein-coding genes in plant defenses against fungal infections. This research demonstrates the potential of publicly available RNA-seq data for identifying the core genes involved in defending against multiple fungal pathogens.