scCUTseq is a versatile framework for spatially resolved single-cell genomic analyses of intratumor heterogeneity

Abstract Chromosomal instability and copy number alterations (CNAs) are pervasive in human cancers. However, the exact timing and mechanism of CNA formation during carcinogenesis remain poorly understood. Here, we describe scCUTseq, an agile and robust workflow for spatially resolved single-cell CNA profiling which could be applied to characterize the CNA landscape in tumor samples. Importantly, scCUTseq could clearly resolve the copy number profiles of different cell lines and was free of cross-contamination, highlighting its specificity. Secondly, we assessed the sensitivity of scCUTseq by determining its ability to detect a 7Mb deletion induced by CRISPR-Cas9 in a small percentage (~3%) of cells transfected with two small guide RNAs (sgRNA) targeting the KMT2A and HYLS1 locus on chr11. In 3.3% of the cells transfected with both sgRNAs, scCUTseq detected a single copy of the exact 7 Mb deletion, in line with the quantification by FISH, highlighting the sensitivity of our method. Lastly, to rule out the artifacts introduced by the MALBAC step, we compared scCUTseq with Acoustic Cell Tagmentation (ACT), another single-cell SCNA profiling method that is based on DNA tagmentation and does not involve a whole genome amplification (WGA) step. Both visual and quantitative comparisons revealed that the genome-wide copy number profiles obtained by either method were highly similar, indicating that the WGA step in scCUTseq does not result in obvious artifact CNA calls. scCUTseq is a versatile and scalable method, which can greatly facilitate the depiction of the single-cell CNA profile in cancers.