Cas9 targeted enrichment for Nanopore sequencing

Full Project Title

CRISPR/CAS9-assisted ONT sequencing for gene targeting: A rapid, selective and cost-effective approach for the characterisation of genetic and epigenetic variation

Project Summary

One of the challenges of short-read sequencing technologies is to study structural and copy number variations over thousands of bases. Third-generation sequencing platforms such as PacBio and Oxford Nanopore Technologies (ONT) provide a great opportunity for these types of variations based on their abilities to produce longer reads. However, these technologies suffer from low sequencing throughput which then requires deep sequencing, incurring significant costs. Therefore, there is a need for a fast, cost-effective, flexible approach for characterising these challenging regions.

Nanopore Cas9-targeted sequencing combines long-read nanopore sequencing with Cas9-guide RNA technology for targeted enrichment sequencing, allowing for selective sequencing of regions of interest at higher coverage. This approach allows the user to target sequences up to 50kb in a single assay. As the protocol requires no PCR amplification, this strategy also provides an opportunity to simultaneously measure methylation patterns within the region of interest. This project will evaluate and adapt the targeted Cas9 sequencing protocol for different types of targets and organisms, resulting in an optimised protocol for enrichment sequencing with Oxford Nanopore Technologies.

Potential Outcomes

The expected outcome for this project is an optimised protocol for Cas9-targeted sequencing with recommendations for the quality and quantity of purified DNA extracts, crRNA design and screening, and library preparation method. To ensure the protocol can be used widely across UQ and the broader scientific community, associated open-access software and analysis pipelines will be developed so that researchers can make the most effective use of the method. The bioinformatics pipelines will be compatible with UQ computing infrastructure and will include code for evaluating the performance of guides, and initial data analysis including phasing, base modification calling and visualisation of the results.