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Updated: Mar 12, 2026

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

Complete Transcriptome RNA-Seq.

David F B Miller¹, Pearlly Yan², Fang Fang³

¹Medical Sciences Program, Indiana University School of Medicine, 1001 East 3rd Street, Bloomington, IN, 47405, USA. millerdf@indiana.edu.

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

|November 4, 2016

Summary

This summary is machine-generated.

This study presents a new RNA-Seq protocol for accurate gene expression analysis, even with degraded RNA samples. The method enhances transcriptome profiling from low-quantity inputs using duplex-specific nuclease (DSN) technology.

Keywords:

Duplex-specific Nuclease Gene Expression RNA-Seq Sequencing Transcriptome

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Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

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Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA

Published on: October 27, 2011

Area of Science:

Molecular Biology
Genomics
Transcriptomics

Background:

RNA sequencing (RNA-Seq) is crucial for global gene expression analysis.
Intact RNA is often compromised in samples due to fixation or degradation, limiting current RNA-Seq accuracy.
Existing protocols struggle with quantifying gene expression from degraded or low-quantity RNA inputs.

Purpose of the Study:

To develop an improved RNA-Seq protocol for accurate whole-transcriptome gene expression quantification.
To address limitations in analyzing degraded or low-quantity RNA samples.
To ensure compatibility with major sequencing platforms like Illumina.

Main Methods:

Developed a novel RNA-Seq protocol incorporating restructured adapter sequences for Illumina platforms (HiSeq, MiSeq, NextSeq).
Utilized duplex-specific nuclease (DSN) to efficiently remove ribosomal RNA (rRNA).
Retained diverse RNA types for comprehensive transcriptome profiling, even with limited input material.

Main Results:

The protocol effectively quantifies gene expression from whole transcriptomes, including degraded samples.
DSN treatment successfully removed abundant rRNA, enabling superior transcriptome profiling.
Generated sequencing libraries compatible with multiple Illumina platforms.

Conclusions:

The developed RNA-Seq protocol overcomes limitations of existing methods for analyzing compromised RNA samples.
This approach enables accurate gene expression analysis from low-quantity and degraded RNA.
The protocol offers a versatile solution for transcriptome profiling adaptable to various sequencing platforms.