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Related Experiment Videos

An evaluation of linear RNA amplification in cDNA microarray gene expression analysis.

Bingmei Zhu1, Feng Xu, Yoshinobu Baba

  • 1Department of Molecular and Pharmaceutical Biotechnology, Graduate School of Pharmaceutical Sciences, The University of Tokushima, CREST, JST, The 21st Century COE Program, Shomachi-1, Tokushima 770-8505, Japan. bingmeizhu@yahoo.co.jp

Molecular Genetics and Metabolism
|October 11, 2005
PubMed
Summary

This study shows that T7-based linear amplification can successfully amplify low amounts of total RNA for DNA microarray analysis. This method generates gene expression profiles comparable to unamplified RNA, enabling sensitive gene expression studies.

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Area of Science:

  • Biomedical Sciences
  • Molecular Biology
  • Genomics

Background:

  • DNA microarrays are essential tools in biomedical research.
  • A key limitation is the need for substantial RNA quantities.
  • Low RNA input hinders comprehensive gene expression profiling.

Purpose of the Study:

  • To evaluate a T7-based linear amplification kit for low RNA input.
  • To compare gene expression profiles from amplified and unamplified RNA.
  • To assess the reproducibility and comparability of the amplification method.

Main Methods:

  • Utilized an Agilent low RNA input fluorescent linear amplification kit.
  • Amplified 0.2 µg of total RNA to amplified aRNA.
  • Compared gene expression profiles using DNA microarrays.

Related Experiment Videos

  • Validated results with quantitative real-time PCR for 10 genes.

    • Main Results:

    • Reproducible amplification of nanogram quantities of total RNA was achieved.
    • Gene expression profiles from amplified aRNA were comparable to unamplified total RNA.
    • Quantitative real-time PCR showed good correlation with amplified aRNA microarray data.

    Conclusions:

    • T7-based linear amplification is effective for low RNA input DNA microarray analysis.
    • This technique enables reliable gene expression profiling from minimal samples.
    • The method supports sensitive and comparable gene expression studies in biomedical research.