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Related Concept Videos

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.
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Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jun 21, 2026

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations
11:52

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

Published on: August 4, 2016

Serial analysis of gene expression: probing transcriptomes for molecular targets.

A Lal1, I M Sui, G J Riggins

  • 1Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA.

Current Opinion in Molecular Therapeutics
|July 25, 2009
PubMed
Summary

Serial analysis of gene expression (SAGE) provides a digital transcriptome profile by counting RNA transcripts. This method identifies disease-associated genes for targeted therapy development.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Serial analysis of gene expression (SAGE) is a technique for quantifying gene expression levels.
  • Understanding gene expression is crucial for deciphering cellular functions and disease mechanisms.

Purpose of the Study:

  • To describe the Serial analysis of gene expression (SAGE) methodology.
  • To highlight the application of SAGE in identifying disease-related genes and informing therapeutic strategies.

Main Methods:

  • Isolation of small RNA transcript tags.
  • Cloning of tags into sequencing vectors.
  • Automated sequencing for efficient tag counting and digital transcriptome generation.

Main Results:

  • SAGE generates a digital, fractional representation of the cellular transcriptome.
  • Comparison of SAGE libraries reveals differentially expressed genes.
  • Identification of genes implicated in disease pathogenesis.

Conclusions:

  • SAGE enables comprehensive transcriptome analysis.
  • Differentially expressed genes identified via SAGE can serve as biomarkers for disease.
  • Insights from SAGE facilitate the development of targeted gene or pathway therapies.