Abstract
AbstractAn effective tool for discovering differentially expressed genes (DEGs) related to late blight (LB) resistance is the transcriptome sequencing of potatoes. The aim of this study was to compare transcriptome expression analysis in incompatible and compatible interactions via high-throughput sequencing. Furthermore, we performed a bioinformatics analysis to screen a large number of specific transcription factors (TFs) and DEGs linked to Phytophthora infestans infection. Two locally cultivated potato varieties were chosen from evaluation assays conducted in two consecutive seasons and based on the disease severity (DS) values. These varieties were the highly resistant Jelly (HR) to P. infestans and the moderately susceptible Annabelle (MS). Ribonucleic acid-sequencing (RNA-seq) was achieved for the two varieties with their controls through the BGISEQ-500 sequencing platform. The RNA-seq analysis identified P. infestans-responsive genes and their expression in potatoes. The mechanism of the response of these cultivars to the P. infestans pathogen by TFs and DEG genes, which play an important role in defense response, was investigated. The Gene Ontology (GO) analysis classified 46,248 unigenes in the HR and 26,921 unigenes in MS into the following three categories: biological process, cellular component, and molecular functions. More genes were responsible for the cellular component category, biological process, and molecular functions in HR compared to MS. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the significantly enriched DEGs were included in the plant–pathogen interaction, biosynthesis of secondary metabolites, and ribosome. In addition, 1874 transcription factor genes belonging to 85 families were indicated in the DEGs, of which MYB and AP2-EREBP genes were the most abundant. Besides, multiple genes related to LB resistance showed differential expression during infection. It also sheds light on the molecular mechanisms behind potato resistance to P. infestans infection.
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