A Novel Next-Generation Sequencing and Analysis Platform to Assess the Identity of Recombinant Adeno-Associated Viral...

Recombinant adeno-associated virus (rAAV) vectors are increasingly popular gene delivery tools in biological systems. They are safe and lead to high-level, long-term transgene expression. rAAV are available in multiple serotypes, natural or engineered, which enable targeting to a wide array of tissues and cell types. In addition, rAAVs are relatively easily produced in a well-equipped lab or obtained from a viral vector core facility. Unfortunately, there is no standardization of quality control assays beyond titering and purity assessments. Next-generation sequencing (NGS) can be used to identify rAAV preparations. Because the rAAV genome is single stranded, previous studies have assumed that rAAV genomes must be converted to double strands before NGS. We demonstrate that rAAV DNA extracts exist primarily as double-stranded species. We hypothesize that these molecules form from the natural base pairing of complementary [+] and [-] strands after DNA extraction and show that rAAV DNA extracts are sufficient templates for downstream NGS without the labor-intensive double-stranding step. Here, we provide a detailed protocol for the simple and rapid NGS of rAAV genomes from DNA extracts. With this protocol, users can quickly confirm the identity of an rAAV preparation and detect the presence of contaminating rAAV DNA. In addition, we share custom Python scripts that allow users to accurately determine the serotype and detect Cre-independent DNA recombination events in rAAV containing Lox sites within minutes. We have used these scripts to analyze more than 100 rAAV preparations. Although we focused on the detection of cross-contaminating rAAV DNA and recombination events, our Python scripts can be customized to detect other sequences or events, such as reverse packaging of plasmid backbone or DNA from the packaging cell line. We find that the NGS of rAAV DNA extracts, termed viral genome sequencing, is a simple and powerful method for rAAV validation.