Single-cell template strand sequencing of micronucleated cells from spontanteous mitotic errors and targeted double-strand break induction, in untransformed near-diploid cell lines.
Mitotic errors play a fundamental role in cancer genome evolution, producing widespread structural and numerical chromosomal abnormalities (CAs). These errors often result in the formation of micronuclei, atypical nuclear structures where DNA can fragment and undergo complex rearrangements, making them valuable biomarkers for cells undergoing de novo CA formation. In this study, we employed machine learning-assisted genomics-and-imaging convergence (MAGIC), an autonomous platform that couples automated imaging and single-cell genomics, to isolate micronucleated cells and study de novo CA formation at scale. We explore the CA landscape in an untransformed, near-diploid cell line with both functional and impaired TP53, as well as after inducing targeted double-strand breaks using CRISPR-Cas9.