Overview
Single-cell RNA sequencing (scRNA-seq) measures the transcriptome of individual cells, providing unprecedented resolution of cellular heterogeneity. Bulk RNA-seq averages gene expression across millions of cells, masking the distinct transcriptional states of different cell types. In contrast, scRNA-seq captures the expression profile of each cell separately, enabling the discovery of rare cell populations, the reconstruction of developmental trajectories, and the characterization of cell-type-specific responses. Since the first scRNA-seq study in 2009, the technology has advanced rapidly, with modern platforms profiling tens of thousands of cells in a single experiment.
Methods
The scRNA-seq workflow involves cell isolation (using droplet-based platforms such as 10x Genomics Chromium, microfluidics like Fluidigm C1, or plate-based methods), reverse transcription with unique molecular identifiers (UMIs) to remove amplification bias, and library preparation for sequencing. Bioinformatics analysis proceeds through: quality control (filtering cells by gene count, mitochondrial content, and UMI counts), normalization (SCTransform, scran, or BASiCS), batch correction (Harmony, Seurat’s CCA, or scVI), dimensionality reduction (PCA followed by UMAP or t-SNE visualization), clustering (Louvain or Leiden algorithms), and differential expression between clusters. Cell type annotation uses marker genes and reference databases.
Applications
scRNA-seq has transformed multiple fields. It has created comprehensive cell atlases for human organs, mapped the developing embryo, and revealed previously unknown cell subtypes in the brain and immune system. In cancer research, scRNA-seq dissects tumor heterogeneity and the tumor microenvironment, identifying rare drug-resistant cell states related to flow cytometry markers. The technique builds on core RNA sequencing principles and DNA microarrays and gene expression concepts. Emerging spatial transcriptomics methods now add positional context to single-cell data, revealing how cells organize within tissues.
