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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...

Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
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Related Experiment Video

Updated: Dec 9, 2025

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

Single-cell sequencing techniques from individual to multiomics analyses.

Yukie Kashima^1,2, Yoshitaka Sakamoto¹, Keiya Kaneko¹

¹Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.

Experimental & Molecular Medicine

|September 15, 2020

Summary

This summary is machine-generated.

Single-cell sequencing offers powerful tools for analyzing genomics, epigenomics, and transcriptomics. These advanced methods enable detailed molecular profiling of individual cells for research and disease understanding.

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Last Updated: Dec 9, 2025

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

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

Published on: January 7, 2020

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

Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

Single-cell sequencing is revolutionizing biological research.
Understanding cellular heterogeneity is crucial for basic science and disease study.

Purpose of the Study:

To review single-cell sequencing techniques for multiomics profiling.
To highlight applications in genomics, epigenomics, and transcriptomics.
To discuss computational and experimental integration methods for multi-omics data.

Main Methods:

Review of single-cell genomic, epigenomic, and transcriptomic sequencing methods.
Description of computational approaches for integrating multi-omics data (e.g., scRNA-seq, scATAC-seq).
Overview of experimental techniques for simultaneous multi-omics measurements in single cells.

Main Results:

Detailed descriptions of various single-cell sequencing techniques are provided.
Examples of their applications in biological research are presented.
Methods for integrating diverse single-cell omics data are discussed.

Conclusions:

Single-cell sequencing techniques provide deep insights into cellular molecular profiles.
These methods are essential for understanding both normal biological processes and disease states.
The integration of multi-omics data from single cells enhances comprehensive cellular analysis.