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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...
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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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DNA Microarrays02:34

DNA Microarrays

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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Genomics

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Related Experiment Video

Updated: Jun 29, 2026

Cost-Efficient Transcriptomic-Based Drug Screening
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Cost-Efficient Transcriptomic-Based Drug Screening

Published on: February 23, 2024

SuperSAGE: a modern platform for genome-wide quantitative transcript profiling.

Hideo Matsumura1, Detlev H Krüger, Günter Kahl

  • 1Iwate Biotechnology Research Center, Narita 22-174-4, Kitakami, Iwate, 024-0003, Japan. hideoma@ibrc.or.jp

Current Pharmaceutical Biotechnology
|October 16, 2008
PubMed
Summary
This summary is machine-generated.

SuperSAGE, a transcript profiling technique, offers longer tags for accurate gene annotation in any organism. Its combination with Next Generation Sequencing creates a superior transcriptome analysis platform.

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Serial Analysis of Gene Expression (SAGE) enables transcript profiling.
  • Previous SAGE versions had limitations in tag length and annotation accuracy.

Purpose of the Study:

  • Introduce SuperSAGE, an enhanced SAGE variant.
  • Highlight its advantages for transcript profiling and gene annotation.
  • Showcase its applicability to diverse organisms and its integration with new sequencing technologies.

Main Methods:

  • Utilizes 26-bp tags derived from cDNA using the EcoP15I restriction enzyme.
  • Employs BLAST searches for gene identification in model organisms.
  • Applies 3 eal- or 5 eal-RACE for primer design in non-model organisms.
  • Integrates with Next Generation Sequencing (NGS) for advanced transcriptome analysis.

Main Results:

  • SuperSAGE provides the longest tags among SAGE variants, facilitating precise tag-to-gene mapping.
  • Enables transcript profiling in both model and non-model organisms.
  • Facilitates applications like "interaction transcriptome" and "SuperSAGE array".
  • The combination of SuperSAGE and NGS establishes a novel transcriptome platform.

Conclusions:

  • SuperSAGE significantly improves transcript profiling and gene annotation accuracy.
  • It offers a versatile and cost-effective transcriptome analysis solution.
  • The SuperSAGE-NGS platform surpasses traditional microarray-based methods in throughput and data quality.