Format

Send to

Choose Destination
Cell Syst. 2018 Feb 28;6(2):171-179.e5. doi: 10.1016/j.cels.2018.01.014. Epub 2018 Feb 14.

Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH.

Author information

1
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
2
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
3
Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
4
Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
5
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
6
Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
7
Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: jmurr@mail.med.upenn.edu.
8
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: arjunrajlab@gmail.com.

Abstract

Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. Here, we use single-molecule RNA fluorescence in situ hybridization as a gold standard to assess trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We quantified the gene expression distribution for 26 genes that range from ubiquitous to rarely expressed and found that the correspondence between estimates across platforms improved with both transcriptome coverage and increased number of cells analyzed. Further, by characterizing the trade-off between transcriptome coverage and number of cells analyzed, we show that when the number of genes required to answer a given biological question is small, then greater transcriptome coverage is more important than analyzing large numbers of cells. More generally, our report provides guidelines for selecting quality thresholds for single-cell RNA-sequencing experiments aimed at rare cell analyses.

KEYWORDS:

single molecule RNA FISH; single-cell RNA sequencing; single-cell analysis

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center