single-cell sequencing

Definition

Single-cell sequencing is a high-throughput genomic technique that analyzes molecular profiles (RNA, DNA, proteins, or chromatin accessibility) at the individual cell level, rather than from bulk tissue samples. This methodology reveals cellular heterogeneity within tissues, identifies rare cell populations, and tracks developmental trajectories or disease progression at unprecedented resolution. Key technologies include scRNA-seq (transcriptomics), scATAC-seq (chromatin accessibility), and scDNA-seq (genomics). By capturing cell-to-cell variation, single-cell sequencing enables researchers to construct cellular atlases, discover novel cell types, understand differentiation pathways, and identify disease-specific cellular states that would be masked in traditional bulk sequencing approaches.

Visualize single-cell sequencing in Nodes Bio

Researchers can visualize single-cell sequencing data as cell-cell similarity networks, where nodes represent individual cells clustered by expression profiles. Gene regulatory networks can be inferred from scRNA-seq data to reveal transcription factor-target relationships. Cell trajectory networks map differentiation pathways, while cell-type-specific protein interaction networks identify molecular mechanisms unique to particular cellular populations discovered through single-cell analysis.

Example Use Case

A cancer research team uses scRNA-seq to profile 50,000 tumor cells from glioblastoma patients. They discover a rare, drug-resistant cell population comprising only 2% of cells. By constructing gene regulatory networks specific to this subpopulation, they identify a master transcription factor driving resistance. Network analysis reveals this factor activates a cascade of survival genes, providing a novel therapeutic target. The team validates their findings by perturbing this network node in patient-derived organoids, successfully sensitizing resistant cells to chemotherapy.

Related Terms