SciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution. Issue 1 (15th October 2021)

• Record Type: Journal Article
• Authors: Mahdipour-Shirayeh, Ali; Erdmann, Natalie; Leung-Hagesteijn, Chungyee; Tiedemann, Rodger E
• Is Part Of: Briefings in bioinformatics. Volume 23:Issue 1(2022)
• Publication Date: 2021-10-15
• Subjects: single-cell RNA sequencing (scRNA-seq) -- copy number variation (CNV) -- normalization -- multi-omics -- multiple myeloma -- RTAM -- sciCNV; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbab413
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: Chromosome copy number variations (CNVs) are a near-universal feature of cancer; however, their individual effects on cellular function are often incompletely understood. Single-cell ribonucleic acid (RNA) sequencing (scRNA-seq) might be leveraged to reveal the function of intra-clonal CNVs; however, it cannot directly link cellular gene expression to CNVs. Here, we report a high-throughput scRNA-seq analysis pipeline that provides paired CNV profiles and transcriptomes for single cells, enabling exploration of the effects of CNVs on cellular programs. RTAM1 and -2 normalization methods are described, and are shown to improve transcriptome alignment between cells, increasing the sensitivity of scRNA-seq for CNV detection. We also report single-cell inferred chromosomal copy number variation (sciCNV), a tool for inferring single-cell CNVs from scRNA-seq at 19–46 Mb resolution. Comparison of sciCNV with existing RNA-based CNV methods reveals useful advances in sensitivity and specificity. Using sciCNV, we demonstrate that scRNA-seq can be used to examine the cellular effects of cancer CNVs. As an example, sciCNV is used to identify subclonal multiple myeloma (MM) cells with +8q22–24. Studies of the gene expression of intra-clonal MM cells with and without the CNV demonstrate that +8q22–24 upregulates MYC and MYC-target genes, messenger RNA processing and protein synthesis, which is consistent with established models. In conclusion, we provide new tools for scRNA-seq that enable paired profiling of the CNVs and transcriptomes of single cells, facilitating rapid and accurate deconstruction of the effects of cancer CNVs on cellular programming.