RESUMO
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.
Assuntos
Proteínas de Arabidopsis , Arabidopsis , Micoses , Arabidopsis/genética , Arabidopsis/microbiologia , RNA-Seq , Proteínas de Arabidopsis/genética , Plantas/genéticaRESUMO
RNA sequencing (RNA-seq) coupled to DNA methylation strategies enables the detection and characterization of genes which expression levels might be mediated by DNA methylation. Here we describe a bioinformatics protocol to analyze gene expression levels using RNA-seq data that allow us to identify candidate genes to be tested by bisulfite assays. The candidate methylated genes are usually those that are low expressed in a particular condition or developmental stage.