Transcriptional dynamics study of resistant host peanut plant against foliar disease to reveal molecular insights involved in resistance

Abstract

newlineAmong biotic stresses, several diseases, including rust caused by Puccinia arachidis and early leaf spot (ELS) caused by Cercospora arachidicola are global constraints leading to 50% yield losses for peanut production. The use of a fungicide is not a viable option economically and it is unsafe for human health as well as the environment. The development and characterization of naturally-resistant host-plant species is the most effective approach. To understand the plant-pathogen interaction comprehensively, it is valuable to monitor the gene expression profiles of both the interacting organisms simultaneously in the same infected plant tissue. newlineIn this study, we used RNA-Seq to analyse the expression profile of resistant (GPBD-4) and susceptible (JL-24) genotypes of peanut plant against P. arachidis and C. arachidicola infection. Gene Ontology and KEGG analysis of Differentially expressed genes (DEGs) revealed essential genes and their pathways responsible for defense response of peanut plants against fungal pathogens. The majority of the transcripts were assigned to plant-pathogen interaction pathways, metabolic pathways, MAPK signalling pathway, plant hormone signal transduction, phenylalanine metabolism and biosynthesis of secondary metabolites-related pathways. The resistant variety was able to withstand biotic stress due to exclusive up-regulation of defense-related genes (pathogenesis-related (PR) proteins, thaumatin, glutathione peroxidase, ethylene-responsive factor and F-box). On the other hand, the susceptible variety was more prone to damage by infection due to down-regulation of genes including (beta-glucosidase, cytochrome p450, Leucine-rich repeat protein kinase, transcription factors (WRKY, bZIP, MYB and terpene synthase) associated with a majority of biological function. This finding was also supported by expression data generated by RT-qPCR analysis. RNA-Seq analysis data for both the diseases were validated by RT-qPCR using 15 randomly selected primer sets derived from DEGs. A high