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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Apr 8, 2026

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Single-cell RNA-Seq of Defined Subsets of Retinal Ganglion Cells

Published on: May 22, 2017

A primer on single-cell RNA-seq analysis using dendritic cells as a case study.

Giulia Protti¹, Roberto Spreafico²

¹Department of Biotechnology and Biosciences, University of Milano-Bicocca, Milan, Italy.

|September 8, 2024

Summary

This summary is machine-generated.

Single-cell transcriptomics reveals complex dendritic cell (DC) subsets. This review guides immunologists through single-cell RNA sequencing (scRNA-seq) methods for deeper understanding of DC biology.

Keywords:

DCs bioinformatics dendritic cells scRNA‐seq single‐cell transcriptomics

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Area of Science:

Immunology
Genomics
Computational Biology

Background:

Single-cell transcriptomics has transformed immunology.
Dendritic cells (DCs) are crucial immune cells with complex subsets.
Understanding DC heterogeneity is key to immune research.

Purpose of the Study:

To provide immunologists with a guide to single-cell transcriptomic analysis.
To highlight recent advances in dendritic cell (DC) biology.
To demystify computational methods for scRNA-seq data.

Main Methods:

Review of recent single-cell RNA sequencing (scRNA-seq) studies.
Analysis of computational tools and methodologies for scRNA-seq.
Synthesis of findings from pioneering DC research.

Main Results:

scRNA-seq has uncovered significant complexity and heterogeneity in DC subsets.
Computational techniques have greatly advanced the study of DC biology.
Established benchmarks and tutorials aid in scRNA-seq data analysis.

Conclusions:

scRNA-seq is a powerful tool for dissecting DC heterogeneity and function.
This review equips researchers to utilize scRNA-seq for immunological discovery.
Leveraging scRNA-seq advances DC biology and broader immunology research.