Cell sorting based on single nucleotide variation enables characterization of mutation-dependent transcriptome and chromatin states.

Point mutations in oncogenes and tumor suppressor genes are common drivers of tumorigenesis. Moreover, single nucleotide variants (SNVs) also contribute to cancer by altering the noncoding regions of the genome. However, connecting SNVs to transcriptomic and epigenetic changes at the single-cell level remains challenging. To enable studies of rare populations of cells harboring specific point mutations, we developed STAR-FACS [Specific-To-Allele polymerase chain reaction (PCR) - fluorescence-activated cell sorting (FACS)]. This method allows for cell labeling based exclusively on genomic allele alteration, by in-cell DNA amplification. Labeled cells are then sorted and profiled with bulk or single cell transcriptomics. The labeling method is also compatible with downstream characterization of chromatin features with CUT&Tag (Cleavage Under Targets and Tagmentation). Our proof-of-principle study shows that STAR-FACS can be used to separate cells based on TERT promoter mutation status and is applicable to primary cell lines and dissociated solid tumor tissue. We demonstrate that glioblastoma cell lines derived from the same tumor but harboring distinct TERT promoter SNVs have different transcriptional programs. STAR-FACS provides a novel tool for studies linking subclonal noncoding SNVs with transcriptomic and epigenetic heterogeneity.