Computational and molecular tools for scalable rAAV-mediated genome editing

Area of Science:

• Molecular Biology
• Genomics
• Bioinformatics

Background:

• Large-scale cancer genomics studies identify numerous driver mutations requiring cellular phenotype characterization.
• Recombinant adeno-associated virus (rAAV)-mediated gene targeting is a valuable genome editing technique but is often time-consuming and labor-intensive.
• Efficient generation of gene targeting constructs is crucial for advancing functional genomics in cancer research.

Purpose of the Study:

• To develop a software and vector system for automated design and generation of optimized rAAV gene targeting constructs.
• To facilitate the knock-in of single nucleotide substitutions and knock-out of genes in human cells using rAAV.
• To reduce the time and labor associated with rAAV-mediated gene targeting.

Main Methods:

• Development of novel software utilizing computational approaches for designing rAAV targeting constructs.
• Creation of automation-friendly vector tools, including a Gateway-based cloning system, for construct generation.
• Application of developed tools for designing constructs targeting protein-coding exons and genes for knock-out.

Main Results:

• Computational design enabled the creation of rAAV constructs for editing approximately 71% of bases in protein-coding exons.
• Approximately 81% of human genes were predicted to be targetable by rAAV-mediated knock-out.
• A Gateway-based cloning system facilitated robotic automation and successful generation of targeting constructs.

Conclusions:

• The developed software and vector tools significantly streamline and automate the design and generation of rAAV targeting constructs.
• These tools enable efficient and automated rAAV-mediated gene editing, including construct design, generation, and cell enrichment.
• This advancement accelerates the characterization of cellular phenotypes associated with cancer driver mutations.