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AFLP-based transcript profiling (cDNA-AFLP) for genome-wide expression analysis.

Marnik Vuylsteke1, Johan D Peleman, Michiel J T van Eijk

  • 1Department of Plant Systems Biology, VIB, Technologiepark 927, B-9052 Ghent, Belgium. marnik.vuylsteke@psb.ugent.be

Nature Protocols
|June 5, 2007
PubMed
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This study introduces cDNA-AFLP, a novel method for genome-wide gene expression analysis applicable to any species. This technique enables gene discovery and expression profiling without requiring prior genome sequencing information.

Area of Science:

  • Molecular Biology
  • Genomics
  • Transcriptomics

Background:

  • DNA microarrays are standard for genome-wide expression analysis but require prior sequence knowledge.
  • Existing methods limit expression profiling to well-characterized organisms.

Purpose of the Study:

  • To present a novel protocol for complementary DNA-amplified fragment length polymorphism (cDNA-AFLP) for genome-wide expression analysis.
  • To enable gene expression profiling in any species, irrespective of genome sequencing status.

Main Methods:

  • The protocol involves mRNA reverse transcription to cDNA, restriction digestion, adapter ligation, and selective PCR amplification.
  • Fractionation of cDNA fragments is achieved through selective PCR, followed by separation on high-resolution gels.
  • Visualization uses autoradiography or automated LI-COR systems; differential expression is quantified by band intensity.

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Main Results:

  • cDNA-AFLP provides a measure of relative gene expression levels through observed differences in band intensities.
  • Differentially expressed genes can be identified by purifying and sequencing cDNA-AFLP fragments.
  • The protocol is efficient, completable within 3-4 days.

Conclusions:

  • cDNA-AFLP is a versatile and powerful tool for genome-wide expression analysis and gene discovery.
  • This method overcomes the limitations of sequence-dependent techniques, making transcript profiling accessible across diverse species.
  • Its applications include temporal gene expression analysis and identifying novel genes.