Single cell RNA-Seq analysis

Conventional RNA-seq analysis, conducted on bulk RNA, provides valuable insights but cannot reveal interactions between different cells within a complex biological system. To address this limitation and obtain a high-resolution view of cell-to-cell variation, researchers turn to single-cell RNA sequencing (scRNA-seq), which analyses the transcriptome of individual cells.

Key steps involved in scRNA-seq include:

• Cell isolation: Individual cells are isolated from tissue samples using micromanipulation or microfluidic devices.

• Library preparation: The RNA from each cell is isolated and fragmented, and adapters are added for subsequent sequencing of RNA molecules.

• Sequencing: The cell-specific RNA libraries are then sequenced using NGS technology, typically Illumina sequencing.

• Data processing: The sequencing data is processed to align the reads to a reference genome and to count the number of reads that map to each gene.

• Data analysis: The data is analysed to identify gene expression patterns across different cell types and to cluster cells based on their unique gene expression profiles.

scRNA-seq has many applications, from development studies to investigating diseases and drug responses. It enables the identification of rare cell populations, exploration of cell-to-cell variability, and the discovery of novel cell types and subpopulations. The technique also examines transcriptomic changes in response to treatments, environmental changes, or disease states at the single-cell level.

Single-cell RNA-seq is a sophisticated and technical method requiring specialised equipment, software, and expertise. Additionally, the interpretation of scRNA-seq data demands a profound understanding, given its complexity and potential genetic variations within the data.