Single-cell RNA Sequencing: Introduction, Methods, and Applications

Introduction of single-cell RNA sequencing

Single cell sequencing uses optimized next-generation sequencing (NGS) technology to check the sequence information of a single cell. There is a higher resolution of cell differences and a better understanding of the functions of individual cells in the microenvironment. Sequencing the RNA expressed by a single cell can provide insight into the existence and behavior of different cell types. The population of the same species seems to be cloned genetically, but single-cell RNA sequencing or single-cell epigenetic sequencing can reveal the variability between cells, which can help the population quickly adapt to the changing environment.

The progress and platforms of single-cell RNA sequencing

In 2009, the single-cell RNA sequencing method (scRNA-seq) was developed in the advent of the increasing affordability of sequencing methods. Bulk RNA sequencing usually masks uniqueness and fails to show latent changes in cells. In response to this, scRNA-seq has emerged to uncover this uniqueness, making us see the biology of cells at a finer resolution with defined details. Since its inception, scRNA-seq has been applied to show the dynamics of developmental processes, elucidate novel cell types, identify random allelic gene expression, and determine mechanisms of gene regulation. Commercial platforms include the Fluidigm C1, Wafergen ICELL8, and the 10X Genomics Chromium.

Figure 1. Single-cell isolation and library preparation. (Hwang, 2018)

Single-cell RNA sequencing methods

Several methods, full-length or tag-based, were published under scRNA-seq where each protocol offers its own advantages and applicability. Generally, scRNA-seq includes four steps: (a) single cells or single nuclei isolation and lysis from extracellular matrix and cell-to-cell adhesion, (b) reverse transcription which usually uses oligodT priming for polyadenylated mRNAs and lncRNAs selection, (c) cDNA amplification utilizing SMART-seq and STRT methods, and (d) preparation of library sequencing which is commonly conducted using transposase Tn5- based fragmentation.

The single-cell RNA sequencing method can be applied to various research interests. In organ development, seemingly histologically identical tissues will eventually differentiate in various directions forming specific cell types with unique functions. Through scRNA-seq, understanding of unique gene expression programs that drive differentiation and lineage decisions in cells would improve our understanding of early organ development. In cancer, scRNA-seq allows us to dissect the multiple cell type properties within and surrounding a tumor. Detailed analysis of cell heterogeneity within the primary and metastatic tumors suggested the most appropriate treatment for specific cell cancer types. When scRNA-seq is paired with whole-cell electrophysiological patch-clamp recording, giving rise to Patch-seq, anatomical, morphological, and functional properties could be linked with gene expression.

Challenges and applications

Challenges in scRNA-seq involve working with a limited amount of material (i.e. mRNA); hence, there is a need for amplification methods that may not be always linear such as having biases and errors. Incorporating a unique molecular identifier (UMI) to the scRNA-seq technique helps to overcome this problem. Capturing single cells, the existence of biological noise, and data analysis remain hurdles for the scRNA-seq technology.

Despite the remaining challenges, the future for the scRNA-seq technology remains hopeful. It has an involvement in spatial transcriptomics where the transcriptome could be analyzed in intact tissue sections mounted on slides, without the need for cell isolation from the extracellular matrix. With the help of laser capture microscopy/ dissection, the transcriptome could be analyzed and represent the in vivo scenario to a higher degree than other methods requiring dissociation. Additionally, scRNA-seq allows identification of biomarkers and drug targets which further develops precision medicine and the completion of the human cell atlas. Lastly, combined profiling of the genome, transcriptome, and epigenome from a single cell gave rise to methods such as "DRseq," "scTrio-seq," and "scM&T-seq".

References:

1. Andrews TS, Kiselev VY, McCarthy D, Hemberg M. Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data. Nature Protocols. 2020.
2. Hwang B, Lee JH, Bang D. Single-cell RNA sequencing technologies and bioinformatics pipelines. Experimental & molecular medicine. 2018, 50(8).
3. Hedlund E, Deng Q. Single-cell RNA sequencing: technical advancements and biological applications. Molecular aspects of medicine. 2018, 59.
4. Olsen TK, Baryawno N. Introduction to single‐cell RNA sequencing. Current protocols in molecular biology. 2018, 122(1).
5. Potter SS. Single-cell RNA sequencing for the study of development, physiology and disease. Nature Reviews Nephrology. 2018, 14(8).