Enrichment and analysis of siRNAs for topical RNAi applications.

Full title

Enrichment and analysis of functional small interfering RNAs for optimised topical RNAi applications

Aim

RNA interference (RNAi) is a conserved process that eukaryotes use to regulate transcript abundance in a sequence-specific manner, playing roles in disease defence and maintaining genome stability. Double-stranded RNA (dsRNA) serves as the RNAi trigger molecule that is processed into small interfering RNAs (siRNAs), which direct degradation of complementary RNA transcripts. Exogenous application of dsRNA to induce RNAi is a rapidly growing area of research worldwide, with applications in protection of crops against pests and pathogens, as well as human therapeutics.

Techniques for analysing dsRNA processing are limited, with existing approaches unable to differentiate the functional siRNA molecule from the noise of non-specifically degraded exogenous dsRNA. The aim of this project is to develop and implement techniques for purifying samples enriched in functional siRNAs to gain an enhanced understanding of these fundamental biological processes. Proof-of-concept will be demonstrated using two fungal plant pathogens, with the toolbox established appliable across eukaryotic species. In parallel, bioinformatics capabilities will be developed for analysis of resulting sequencing data to provide key functional and mechanistic insights into exogenous RNAi. Finally, models will be developed to determine whether dsRNA processing can be predicted based on sequence, which would represent a step-change in dsRNA design and efficacy.

Brief project outline

In most eukaryotic organisms, dsRNAs from endogenous or exogenous sources are processed by Dicer enzymes into siRNA duplexes of 21-24 nt in length. These siRNA duplexes are incorporated into the RNA-induced silencing complex (RISC) where one strand of the duplex is degraded. Key components of RISC are catalytic Argonaute (AGO) proteins, which degrade target RNAs in a sequence-specific manner following base-pairing of the incorporated siRNA. Importantly, generation of functional siRNAs from a dsRNA substrate is highly heterogeneous, with some duplexes vastly over-represented in the resulting siRNA pool. Through use of RISC purified RNA samples, functional siRNAs can be identified.

This project will use two complementary biochemical techniques to specifically purify the functional pool of small RNAs generated during dsRNA processing. Following exogenous application, environmental degradation of dsRNAs produces non-functional products that overlap in size with functional siRNAs. The protocols implemented in this project ensure these degradation products are not co-purified andconfound the resulting analyses.

As a set of experimental organisms, fungal plant pathogens, will be used. Processing of dsRNAs will be analysed for these pathogens using in vitro and in planta assays, with guidance from GIH on sample and low-input library preparation for small RNA sequencing. In parallel, bioinformatics pipelines specifically tuned for the analysis of this data will be developed. As more sequencing data becomes available, these data will be used to train machine learning models for predicting dsRNA processing based on the sequence of the input dsRNA.

Given the increasing global interest in RNAi for crop protection and therapeutics, the availability of these protocols and pipelines is expected to have significant impact on the broader research community and enhance UQ’s strong capabilities as a major player in the emerging exogenous RNAi field.

Genomics-based innovative aspect of proposal

For the first time, robust methods for analysis of dsRNA processing following exogenous dsRNA application will be developed. Previously, degraded dsRNA biproducts have been a major limitation, as they cannot be differentiated from functional small RNAs. Bioinformatics pipelines built on the previously published SCRAM alignment and visualisation package (Fletcher et al, 2018, Bioinformatics) will be developed for analysis of resulting sequencing data. GIH’s bioinformatics capabilities will streamline and inform this process in consultation with our in-house expertise.

Broad applicability of the technique

RNAi is a conserved mechanism in eukaryotes, including fungi, plants, insects, nematodes and animals. Exogenous dsRNA applications are being developed for human therapeutics and protection of crops against insect and nematode pests, as well as fungal and viral pathogens. The techniques and protocols developed during this project will be broadly applicable to each of these use cases and more.

These methods will also be of significant value in understanding and elucidating functional RNAi pathways following exogenous dsRNA application, as well as the applied cases of selecting and designing dsRNAs that enhance the highly-targeted advantages of exogenous RNAi without adverse impacts on non-target organisms.

Bioinformatics analysis pipelines will be open source, platform-independent and have low computational requirements, making them readily usable without high-performance computing infrastructure.