Alignment-free characterization of Inverted Terminal Repeats (ITR) in wild-type and recombinant AAV genomes

This article proposes the development of a novel tool for analyzing the structure and characteristics of recombinant adeno-associated virus (rAAV) vectors during vector production and quality assessment. The tool utilizes dotplots, a graphical method for comparing sequences, and a deep learning-based image classification approach. The focus is on the inverted terminal repeats (ITRs) sequences, which play a critical role in identifying and differentiating AAV types. The tool aims to infer the ITR origin, and improve vector analysis and quality control. The dataset creation process involves generating dotplots of wild-type AAV ITRs and introducing small mutations to simulate biological noise. Future work includes addressing the impact of mutations on vector characteristics to detect major structural anomalies, as well as further analyzing pair-dotplots for vector characterization.