34 352 Recent advances in single-cell transcriptomics are ideally placed to unravel 36 intratumoral heterogeneity and selective resistance of cancer stem cell (SC) 37 subpopulations to molecularly targeted cancer therapies. However, current 38 single-cell RNA-sequencing approaches lack the sensitivity required to 39 reliably detect somatic mutations. We developed a method combining high-40

Summary Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for resolving transcriptional heterogeneity. However, its application to studying cancerous tissues is currently hampered by the lack of coverage across key mutation hotspots in the vast majority of cells; this lack of coverage prevents the correlation of genetic and transcriptional readouts from the same single cell. To overcome this, we developed TARGET-seq, a method for the high-sensitivity detection of multiple mutations within single cells from both genomic and coding DNA, in parallel with unbiased whole-transcriptome analysis. Applying TARGET-seq to 4,559 single cells, we demonstrate how this technique uniquely resolves transcriptional and genetic tumor heterogeneity in myeloproliferative neoplasms (MPN) stem and progenitor cells, providing insights into deregulated pathways of mutant and non-mutant cells. TARGET-seq is a powerful tool for resolving the molecular signatures of genetically distinct subclones of cancer cells.