Project: Characterizing RNA structure heterogeneity and RNA methylation using Nanopore long read sequencing
Recent technological and computational advances have enabled progress within the fields of RNA secondary structure and RNA methylation. On one hand, the combination of DMS-MaPseq with the algorithm DREEM has, for the first time, opened the door to the systematic detection and characterisation of alternative secondary structures for any RNA fragment, whether in-vitro or in viable cells ex-vivo. On the other hand, new bioinformatics methods have considerably improved the precise detection of RNA methylation, using Nanopore sequencing. The goal of this project will be to create a new version of DREEM which will take direct RNA Nanopore sequencing as input, detect the location of the DMS modified bases and deconvolute all the alternative structures based on these modifications. This modified DREEM will be benchmarked using publicly available DMS-Nanopore data containing structural heterogeneity across different isoforms and data generated by the Purcell lab. Cutting edge methods for the detection of RNA methylation will also be implemented to match the methylation patterns with alternative structures. The resulting software will be applied to Sars-CoV-2 and HIV data in order to identify RNA "switches" that constitute ideal targets for new RNA therapeutics. This project is entirely computational and will rely heavily on Python. It is targeted to someone with an interest in bioinformatics.
We are interested in RNA secondary structures in RNA viruses. We are seeking to understand how the recently uncovered plasticity of the structurome interacts and correlates with the epi-transcriptome to play a crucial role in viral replication and pathogenicity. Our aim is to use this understanding to develop novel RNA therapeutics and identify potential target regions.
Purcell Group Current Projects
Master of Biomedical Science