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sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution.
- Source :
- Briefings in Bioinformatics; Jan2022, Vol. 23 Issue 1, p1-15, 15p
- Publication Year :
- 2022
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- DNA copy number variations
RNA
MYC oncogenes
MULTIPLE myeloma
GENE expression
Subjects
Details
- Language :
- English
- ISSN :
- 14675463
- Volume :
- 23
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Briefings in Bioinformatics
- Publication Type :
- Academic Journal
- Accession number :
- 155892297
- Full Text :
- https://doi.org/10.1093/bib/bbab413