Single Cell RNA Sequencing of Rare Immune Cell Populations

  title={Single Cell RNA Sequencing of Rare Immune Cell Populations},
  author={Akira Nguyen and Weng Hua Khoo and Imogen Moran and Peter I. Croucher and Tri Giang Phan},
  journal={Frontiers in Immunology},
Single-cell RNA sequencing (scRNA-Seq) is transforming our ability to characterize cells, particularly rare cells that are often overlooked in bulk population analytical approaches. This has lead to the discovery of new cell types and cellular states that echo the underlying heterogeneity and plasticity in the immune system. Technologies for the capture, sequencing, and bioinformatic analysis of single cells are rapidly improving, and scRNA-Seq is now becoming much more accessible to non… 

Figures from this paper

Application of single-cell RNA sequencing methodologies in understanding haematopoiesis and immunology

This review summarises the most recent studies which applied scRNA-seq to answer outstanding questions in the fields of haematology and immunology and discusses the present challenges and future directions.

Single-Cell Transcriptional Profiling of the Intestinal Epithelium.

The principles of proper experimental design are reviewed and methods for the dissociation of the small intestinal epithelium into single cells followed by fluorescence-activated cell sorting (FACS) and for scRNA-seq using the 10× Genomics Chromium platform are provided.

Single-Cell RNA Sequencing and Its Combination with Protein and DNA Analyses

The efforts of integrating the transcriptome profile with highly multiplexed proteomic and genomic data are thoroughly reviewed with results showing the integrated data being more informative than transcriptome data alone.

From phenotypical investigation to RNA-sequencing for gene expression analysis: A workflow for single and pooled rare cells

This work describes an experimental workflow that allows the transcriptomic investigation of single and pooled OE33 cells undergone to DEPArray analysis and recovery, and will pave the way for novel strategies to characterize gene expression profiles of rare cells, both single-cell and low-resolution input.

High-throughput and single-cell T cell receptor sequencing technologies.

Technological advances to identify TCR sequences, analyze their antigen specificities using experimental and computational tools, and pair TCRs with transcriptional and epigenetic cell state phenotypes in single cells are described.

Recent advances in single‐cell multimodal analysis to study immune cells

This review discusses how mechanisms underpinning the immune system mechanisms have been studied through recent advances in single‐cell multimodal technologies.



Single-cell RNA sequencing to explore immune cell heterogeneity

How scRNA-seq can be used to deconvolve immune system heterogeneity by identifying novel distinct immune cell subsets in health and disease, characterizing stochastic heterogeneity within a cell population and building developmental 'trajectories' for immune cells is discussed.

Quantitative assessment of single-cell RNA-sequencing methods

It is shown that single-cell RNA-seq can be used to perform accurate quantitative transcriptome measurement in individual cells with a relatively small number of sequencing reads and that sequencing large numbers of single cells can recapitulate bulk transcriptome complexity.

Quantitative single-cell RNA-seq with unique molecular identifiers

It is shown that molecular labels—random sequences that label individual molecules—can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency.

Identifying cell populations with scRNASeq.

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells

Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

Massively Parallel Single-Cell RNA-Seq for Marker-Free Decomposition of Tissues into Cell Types

An automated massively parallel single-cell RNA sequencing approach for analyzing in vivo transcriptional states in thousands of single cells is introduced and provides the ability to perform a bottom-up characterization of in vivo cell-type landscapes independent of cell markers or prior knowledge.

Full-Length mRNA-Seq from single cell levels of RNA and individual circulating tumor cells

Applying Smart-Seq to circulating tumor cells from melanomas, it is found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type.

Comparative Analysis of Single-Cell RNA Sequencing Methods.

Missing Data and Technical Variability in Single-Cell RNA-Sequencing Experiments

An assessment experiment is used to examine data from published studies and demonstrates that systematic errors can explain a substantial percentage of observed cell-to-cell expression variability, and presents evidence that some of these reported zeros are driven by technical variation.