The improvement and application of topically applied double stranded RNAs to control Sclerotinia sclerotiorum and Hyaloperonospora arabidopsidis
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Date
2022-08-02
Authors
Manchur, Christopher
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Abstract
Hyaloperonospora arabidopsidis and Sclerotinia sclerotiorum are plant pathogens of significance to both agricultural research and production. While chemical pesticides are effective at controlling these pathogens, increasing environmental concerns and pathogen resistance pose serious problems for their continued use. The need to develop environmentally-friendly alternatives is now a major focus for crop protection. RNA interference (RNAi) is a process that utilizes double-stranded RNA to reduce mRNA transcript accumulation and has potential to provide species-specific, sequence-dependent crop protection applications. Using a combination of novel in vitro assays, I identified a set of candidate H. arabidopsidis- and S. sclerotiorum- targeting dsRNAs that reduced germination rates and growth of both pathogens. Using plate-based assays adaptable to high-throughput screening, I screened multiple dsRNAs and demonstrated dsRNA dose-responses within the pathogens. Foliar application of dsRNAs on Arabidopsis thaliana caused transcript knockdown within H. arabidopsidis, confirming that the impaired growth was RNAi-mediated. Comparisons of Dicer gene sequences in H. arabidopsidis and S. sclerotiorum with homologous sequences in other fungi and oomycetes confirmed that while both pathogens shared this conserved RNAi pathway gene, the evolution of Dicer fits with the phylogenetic divergences of these rather different phytopathogens. This research provides valuable insights into novel assays that can be used for evaluating dsRNA treatments in both pathogens, and the optimization of dsRNA treatments can lead towards the development of RNAi-based crop protection products against both downy mildew and Sclerotinia stem rot.
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Keywords
Biotechnology, RNA interference, RNAi, Sclerotinia sclerotiorum, Hyaloperonospora arabidopsidis, Arabidopsis thaliana, Plant Pathology, Bioinformatics