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Related Concept Videos

RNA-seq03:21

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 microarray-based...
Ribosome Profiling02:24

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...

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Related Experiment Video

Updated: May 12, 2026

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA
14:49

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

Published on: October 27, 2011

A new method for stranded whole transcriptome RNA-seq.

David F B Miller1, Pearlly S Yan, Aaron Buechlein

  • 1Medical Sciences, Indiana University School of Medicine, 1001 East 3rd St., Bloomington, IN 47405, United States.

Methods (San Diego, Calif.)
|April 6, 2013
PubMed
Summary
This summary is machine-generated.

This study presents an optimized RNA sequencing protocol using duplex specific nuclease (DSN) for improved whole transcriptome analysis. The method efficiently captures all RNA types, enabling comprehensive gene expression profiling without gel electrophoresis.

Keywords:
DSNDuplex-specific nucleaseFLgRNAGene expressionLgRNARNA-seqTranscriptomeduplex-specific nucleasefragmented LgRNAlarge total RNA >200 ntsmRNAsmall total RNA <200 nt

More Related Videos

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Related Experiment Videos

Last Updated: May 12, 2026

Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA
14:49

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

Published on: October 27, 2011

AQRNA-seq for Quantifying Small RNAs
05:12

AQRNA-seq for Quantifying Small RNAs

Published on: February 2, 2024

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Accurate whole transcriptome sequencing is crucial for understanding gene expression and regulation.
  • Existing RNA sequencing protocols can be inefficient in capturing the full spectrum of RNA molecules.
  • Ribosomal RNA contamination is a common challenge in RNA sequencing library preparation.

Purpose of the Study:

  • To develop an improved protocol for generating stranded, barcoded RNA-seq libraries for comprehensive transcriptome capture.
  • To optimize the use of duplex specific nuclease (DSN) for efficient ribosomal RNA depletion.
  • To enable the detection of diverse RNA types, including coding and non-coding transcripts, without gel electrophoresis.

Main Methods:

  • Optimization of duplex specific nuclease (DSN) treatment for ribosomal RNA removal.
  • Generation of stranded, barcoded RNA-seq libraries.
  • Multiplexed next-generation sequencing (NGS) of prepared libraries.
  • Analysis of diverse RNA species including miRNA, piRNA, snoRNA, lincRNA, mtRNA, and mRNA.

Main Results:

  • Demonstrated improved efficiency in multiplexed NGS by optimizing DSN for ribosomal RNA depletion.
  • Successfully captured the whole transcriptome, detecting expression profiles of all RNA types.
  • Generated high-quality data without the need for gel electrophoresis.
  • Enabled identification of differential expression in coding and non-coding transcripts, splice variants, mitochondrial genes, and SNPs.

Conclusions:

  • The optimized protocol provides a more efficient and comprehensive approach to whole transcriptome RNA sequencing.
  • This method facilitates the discovery of novel transcripts, splice variants, and genetic variations.
  • The protocol is valuable for detailed gene expression analysis across various RNA types.