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

In this study, we validated recombinant adeno-associated viral integration analysis (RAAVioli), a previously published computational method for the comprehensive analysis of adeno-associated virus vector (AAV) integration sites (ISs) and vector rearrangements across both long- and short-read sequencing platforms. Through in silico benchmarking and in vivo validation in a xenogeneic human hepatocyte model transduced with recombinant AAV (rAAV), we demonstrate the robustness and versatility of RAAVioli in accurately identifying AAV-genome junctions and reconstructing complex vector rearrangements across diverse experimental workflows. RAAVioli enables high-resolution detection of chimeric sequences, characterization of integration-site microhomologies and indels, and identification of complex vector structures, including multimeric concatemers. Short-read sequencing provided superior throughput compared to long-read sequencing, uncovering a larger number of integration sites and enabling precise quantification of clonal abundance, an essential parameter for evaluating the safety of gene therapy protocols. Benchmarking analyses further highlighted RAAVioli’s higher sensitivity and accuracy relative to existing tools, establishing it as a reliable and scalable resource for AAV-based gene therapy and genome-editing studies. Moreover, RAAVioli’s ability to profile structural rearrangements extends its utility to AAV vector characterization and quality assessment. RAAVioli is a computational pipeline that enables high-resolution detection of AAV integration sites and vector rearrangements from both long- and short-read sequencing. Validated in vivo and in silico , RAAVioli provides a unified framework for assessing the safety, clonality, and structural integrity of AAV-based gene therapy and genome-editing products.