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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...

Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

Next-generation Sequencing

Next-generation Sequencing

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
Although all next-generation methods use different technologies, they all share a set of standard features....

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Updated: Apr 25, 2026

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

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Published on: March 29, 2024

Introduction to sequencing the brain transcriptome.

Robert Hitzemann¹, Priscila Darakjian², Nikki Walter¹

¹Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, Oregon, USA; Research Service, Veterans Affairs Medical Center, Portland, Oregon, USA.

International Review of Neurobiology

|August 31, 2014

Summary

This summary is machine-generated.

RNA-Seq technology has advanced significantly, offering superior analysis of the brain transcriptome over microarrays. This method provides greater dynamic range and detects noncoding RNAs, advancing our understanding of brain function and disease.

Keywords:

Behavior Brain Next-generation sequencing RNA-seq Transcriptome

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Published on: November 13, 2011

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Published on: November 13, 2011

Area of Science:

Neuroscience
Genomics
Bioinformatics

Background:

Next-generation sequencing (NGS) has been available for a decade, but brain transcriptome sequencing began in 2008.
Early RNA-Seq studies revealed advantages like exon resolution but also challenges with highly expressed genes and complex data analysis.
Significant advancements in RNA-Seq technology and data analysis have occurred over the past six years.

Purpose of the Study:

To review the transition from microarrays to RNA-Seq for brain transcriptome analysis.
To highlight the advantages of RNA-Seq in studying the complexity of the brain transcriptome.
To underscore the potential of RNA-Seq in understanding brain-behavior-disease relationships.

Main Methods:

Comparison of RNA-Seq data with microarray results for mouse whole brain.
Review of various aspects of sequencing the brain transcriptome, including methods-driven chapters and application-focused studies.
Discussion of improvements in RNA-Seq technology and data analysis.

Main Results:

RNA-Seq offers a greater dynamic range compared to microarrays.
RNA-Seq detects both coding and noncoding RNAs, including alternative spliced transcripts.
RNA-Seq facilitates gene network construction and extraction of genotype information, such as nonsynonymous coding single nucleotide polymorphisms.

Conclusions:

RNA-Seq is the preferred method for analyzing the brain transcriptome due to its comprehensive capabilities.
This technology embraces the complexity of the brain transcriptome, aiding in understanding its regulatory code.
RNA-Seq holds substantial potential for informing research on brain-behavior-disease relationships.