A software package developed and validated at The University of Queensland can tailor safe, effective and chemical-free crop protection using RNA interference (RNAi).
The dsRNAmax software designs double-stranded RNA (dsRNA) to target pest and pathogen species while excluding off-target species such as beneficial insects.
The program was developed by PhD candidate Stephen Fletcher and tested by Dr Chris Brosnan and his team in a collaboration with the Department of Primary Industries (DPI) nematology team.
“The idea of the software is it designs a custom dsRNA for a target organism, and we can use it on almost anything across many projects,” Stephen says.
“It will mean you won’t have off-target impacts, and you can add as many off-targets as you like to be excluded,” he adds.
Chris Brosnan says dsRNA triggered RNAi is a mechanism which already exists to regulate genes in most species.
“What we can do is usurp this existing mechanism with dsRNA created by us to target any gene we choose, and use it to control pathogens and pests,” Chris explains.
“In our validation study we used three species of nematode provided by the nematology team at the DPI, as well as an off-target nematode species,” he says.
“The software was able to design a single dsRNA which could target all three, irrespective of the number of copies of the gene we were looking at and have no impact on the off-target nematode.
“We’ve physically demonstrated this software can do what we say it does, which is where this paper stands out.
“As well, our nematode work with DPI is ongoing and very promising.”
Stephen says the next step for dsRNAmax will be to further improve its effectiveness.
“We’ll be using machine learning to improve the design to make our dsRNA five to ten per cent more effective, which would make a huge difference in a production system,” he says.
“It also means we could use less dsRNA, which will bring down the cost.
“It was the collaboration with DPI which got us over the line because without the validation system we would not have been able to publish the software.”
The research was published in NAR Genomics and Bioinformatics.
Expertise and biological material was provided by the DPI team of Wayne O’Neill, Dylan Corner, Jenny Cobon and Tim Shuey.