Simultaneous Profiling of DNA Copy Number Variations and Transcriptional Programs in Single Cells using RNA-seq

Chromosome copy number variations (CNVs) are a near-universal feature of cancer however their specific effects on cellular function are poorly understood. Single-cell RNA sequencing (scRNA-seq) can reveal cellular gene expression however cannot directly link this to CNVs. Here we report scRNA-seq normalization methods that improve gene expression alignment between cells, increasing the sensitivity of scRNA-seq for CNV detection. We also report sciCNV, a tool for inferring CNVs from scRNA-seq. Together, these tools enable dual profiling of DNA and RNA in single cells. We apply these techniques to multiple myeloma (MM) and examine the cellular effects of cancer CNVs +8q23-24 and +1q21-44. Primary MM cells with +8q23-24 upregulate MYC, MYC-target genes, mRNA processing and protein synthesis; but also upregulate DEPTOR and have smaller transcriptomes. MM cells with +1q21-44 instead reconfigure translation and suppress unfolded protein stress whilst increasing proliferation, oxidative phosphorylation and MCL1. Overall, we provide tools that can enhance the analysis of scRNA-seq and help reveal the effects of cancer CNVs on cellular reprogramming.