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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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Updated: Jun 27, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Advanced sequencing-based high-throughput and long-read single-cell transcriptome analysis.

Shanqing Huang¹, Weixiong Shi¹, Shiyu Li¹

¹Discipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.

|April 26, 2024

Summary

This summary is machine-generated.

Single-cell RNA sequencing (scRNA-seq) enables detailed cell analysis. Advancements in next-generation and third-generation sequencing technologies now offer high-throughput, sensitive, and full-length profiling of cellular transcriptomes.

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Last Updated: Jun 27, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing

Published on: May 23, 2018

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

Area of Science:

Molecular Biology
Genomics
Cell Biology

Background:

Cells display significant heterogeneity, crucial for understanding biological systems.
The transcriptome links genotype and phenotype, making single-cell transcriptome profiling vital for identifying cell types, states, and interactions.
Challenges in single-cell transcriptome analysis include low RNA abundance, diversity, and heterogeneous expression.

Purpose of the Study:

To review current methodologies for single-cell transcriptome sequencing.
To highlight advancements in next-generation sequencing (NGS) and third-generation sequencing (TGS) for single-cell RNA sequencing (scRNA-seq).

Main Methods:

Review of state-of-the-art high-throughput and full-length single-cell RNA sequencing (scRNA-seq) platforms utilizing NGS.
Summary of TGS-based long-read scRNA-seq methods.

Main Results:

NGS and TGS technologies have overcome previous limitations in scRNA-seq.
These technologies facilitate high-throughput, sensitive, full-length, and rapid profiling of single-cell RNAs.

Conclusions:

Current sequencing technologies provide powerful tools for comprehensive single-cell transcriptome analysis.
Future perspectives focus on further advancements in analyzing cellular heterogeneity and function.