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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...
Sanger Sequencing01:57

Sanger Sequencing

DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
Next-generation Sequencing03:00

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.
Maxam-Gilbert Sequencing01:05

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
Challenges of the Maxam-Gilbert Method
The...

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Related Experiment Video

Updated: Jun 3, 2026

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications
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RNA sequencing and quantitation using the Helicos Genetic Analysis System.

Tal Raz1, Marie Causey, Daniel R Jones

  • 1Helicos BioSciences Corporation, Cambridge, MA, USA. traz@helicosbio.com

Methods in Molecular Biology (Clifton, N.J.)
|March 25, 2011
PubMed
Summary

Single-molecule sequencing Digital Gene Expression (smsDGE) eliminates length bias in gene expression analysis. This ultra high-throughput method achieves accurate quantitation with fewer reads than traditional RNA-Seq.

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Last Updated: Jun 3, 2026

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RNA Secondary Structure Prediction Using High-throughput SHAPE

Published on: May 31, 2013

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Ultra high-throughput cDNA sequencing (RNA-Seq) offers enhanced sensitivity but suffers from length bias, requiring high read numbers for short transcripts.
  • This length bias in RNA-Seq necessitates extensive sequencing to accurately quantify short, low-expressed genes.

Purpose of the Study:

  • To introduce single-molecule sequencing Digital Gene Expression (smsDGE), an ultra high-throughput sequencing approach designed to eliminate length bias in gene expression analysis.
  • To demonstrate the efficiency of smsDGE, showing it can achieve equivalent quantitation accuracy to RNA-Seq with significantly fewer reads.

Main Methods:

  • Developed smsDGE, generating a single sequence read per transcript molecule to overcome length bias.
  • RNA is reverse-transcribed to cDNA, tailed, and hybridized to a Helicos single-molecule sequencing Flow-Cell.
  • Sequencing is performed on the Helicos Genetic Analysis System, processing 50 samples simultaneously with 10-20 million reads per sample.

Main Results:

  • smsDGE achieves accurate gene quantitation without the length bias inherent in traditional RNA-Seq.
  • Equivalent quantitation accuracy for the yeast transcriptome was achieved using smsDGE with only 25% of the reads required by RNA-Seq.
  • The smsDGE protocol avoids PCR, sample-size selection, and ligation, minimizing potential biases.

Conclusions:

  • smsDGE offers a more efficient and less biased method for gene expression analysis compared to RNA-Seq.
  • This technology enables sensitive quantitation of short, low-expressed genes by eliminating length-dependent read distribution.
  • smsDGE facilitates both quantitation of known transcripts and discovery of novel transcripts through alignment to reference genomes or transcriptomes.