Powdery mildew (PM) caused by Podosphaera xanthii and downy mildew (DM) caused by Pseudoperonospora cubensis are two of the most economically important diseases for watermelon (Citrullus lanatus) and squash (Cucurbita pepo, C. maxima and C. moschata). Traditional breeding for resistance to PM and DM is resource intensive, often requiring decades' long phenotyping and selection processes. As an alternative, durable and broadspectrum resistance to PM and DM can be obtained through loss-of-function of susceptibility genes in elite breeding material. Susceptibility genes for PM [Mildew-Locus-O (MLO) and Powdery Mildew Resistance (PMR)] and DM [Downy Mildew Resistance (DMR)] have been functionally proven in model plant species. Previous studies have reported candidate MLO genes for C. lanatus and C. pepo, but none for C. maxima and C. moschata. On the contrary, no PMR or DMR candidate genes have been identified for C. lanatus or any of the Cucurbita species. The current study used bioinformatics approaches based on sequence similarity, phylogenetic relationships and presence of conserved domains to predict candidate MLO genes in C. maxima and C. moschata and PMR and DMR genes in C. lanatus, C. pepo, C. maxima and C. moschata. Four MLO homologs in C. maxima and five in C. moschata clustered within Clade V, a clade containing all MLO susceptibility genes in dicots, and had highly conserved transmembrane domains and C-terminal PM interaction motif. Sixty-three candidate PMR genes were identified among the four species, 16 of which had close similarity to functionally proven PMR homologs in model species. Similarly, 37 candidate DMR genes were identified 12 among which clustered with functionally proven DMR homologs in model species. Functional analysis of the genes identified in the current study will reveal their role in pathogenesis and assess their potential for manipulation through gene editing methods to generate novel resistant plant genotypes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.