RAAVioli: A comprehensive approach to characterizing AAV vector integrations and rearrangements

Area of Science:

• Molecular Biology
• Bioinformatics
• Gene Therapy

Background:

• Adeno-associated virus (AAV) vectors are crucial for gene therapy, but understanding their integration into host genomes is vital for safety and efficacy.
• Accurate analysis of AAV integration sites (ISs) and vector rearrangements is essential for preclinical and clinical gene therapy studies.

Purpose of the Study:

• To validate RAAVioli, a computational method for comprehensive analysis of AAV vector integration sites and rearrangements.
• To assess RAAVioli's performance across different sequencing platforms (long- and short-read) and experimental models.

Main Methods:

• In silico benchmarking of RAAVioli against existing tools.
• In vivo validation using a xenogeneic human hepatocyte model transduced with recombinant AAV (rAAV).
• Analysis of AAV-genome junctions, vector rearrangements, microhomologies, indels, and complex structures like concatemers.

Main Results:

• RAAVioli accurately identifies AAV-genome junctions and reconstructs complex vector rearrangements.
• Short-read sequencing demonstrated higher throughput, identifying more ISs and enabling precise clonal abundance quantification compared to long-read sequencing.
• RAAVioli exhibited higher sensitivity and accuracy than existing tools in benchmarking analyses.

Conclusions:

• RAAVioli is a robust, versatile, and scalable computational resource for analyzing AAV integration sites and vector rearrangements.
• The tool is valuable for evaluating gene therapy safety, characterizing AAV vectors, and assessing vector quality.
• RAAVioli's capabilities support advancements in AAV-based gene therapy and genome-editing research.