Aneuploidy: An opportunity within single-cell RNA sequencing analysis
  • JOE R. DELANEY*
Department of Biochemistry and Molecular Biology, Medical University of South Carolina, Charleston, 29425, USA
* Address correspondence to: Joe R. Delaney, delaneyj@musc.edu
Received 29 April 2021; Accepted 26 May 2021 ; Published online 17 June 2021
Abstract
Single-cell sequencing data has transformed the understanding of biological heterogeneity. While many flavors of single-cell sequencing have been developed, single-cell RNA sequencing (scRNA-seq) is currently the most prolific form in published literature. Bioinformatic analysis of differential biology within the population of cells studied relies on inferences and grouping of cells due to the spotty nature of data within individual cell scRNA-seq gene counts. One biologically relevant variable is readily inferred from scRNA-seq gene count tables regardless of individual gene representation within single cells: aneuploidy. Since hundreds of genes are present on chromosome arms, high-quality inferences of aneuploidy can be made from scRNA-seq datasets. This viewpoint summarizes how utilization of these bioinformatic pipelines can benefit scRNA-seq studies, particularly in oncology wherein aneuploidy is both rampant and a hallmark of the studied disease. Awareness and use of these analytical pipelines will improve each field’s ability to understand the studied diseases. Authors are encouraged to attempt these aneuploid analyses when reporting scRNA-seq data, much like copy-number variants are commonly reported in bulk genome sequencing data.
Keywords
scRNA-seq, Copy-number alterations, Aneuploidy, Cancer