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RNA-seq

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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.
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Updated: Oct 4, 2025

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Improving Small RNA-seq: Less Bias and Better Detection of 2'-O-Methyl RNAs

Published on: September 16, 2019

RNA-Seq Experiment and Data Analysis.

Miyuraj Harishchandra Hikkaduwa Withanage¹, Hanquan Liang², Erliang Zeng^3,4,5,6

¹Division of Biostatistics and Computational Biology, College of Dentistry, University of Iowa, Iowa City, IA, USA.

Methods in Molecular Biology (Clifton, N.J.)

|February 4, 2022

Summary

This summary is machine-generated.

High-throughput RNA sequencing (RNA-Seq) allows detailed transcriptome analysis, including gene expression and novel transcripts. This chapter details RNA-Seq library preparation and data analysis for differential gene expression studies.

Keywords:

Bioconductor Data analysis Differentially expressed genes Next-generation sequencing RNA-Seq Statistical analysis

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

High-throughput RNA sequencing (RNA-Seq) provides deep transcriptome insights.
RNA-Seq can analyze various RNA types beyond messenger RNA (mRNA).
It enables accurate gene expression quantification and isoform abundance estimation.

Purpose of the Study:

To describe a protocol for RNA-Seq library construction for Illumina platforms.
To present a computational pipeline for RNA-Seq data analysis.
To enable differential gene expression analysis in response to treatments.

Main Methods:

RNA-Seq library preparation for Illumina Next-Generation Sequencing (NGS) platforms.
Development of a computational pipeline for RNA-Seq data analysis.
Application of protocols to study differential gene expression.

Main Results:

Detailed methodology for RNA-Seq library construction.
A comprehensive computational pipeline for RNA-Seq data analysis.
Successful application in differential gene expression analysis.

Conclusions:

RNA-Seq is a powerful tool for comprehensive transcriptome analysis.
The described protocols facilitate robust RNA-Seq library preparation and data analysis.
This methodology supports the investigation of gene expression changes in various biological systems.