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Related Experiment Videos

Historical background and anticipated developments.

Bertrand Jordan1

  • 1Marseille-Génopole, Case 901, 13288 Marseille, France. jordan@genopole.univ-mrs.fr

Annals of the New York Academy of Sciences
|January 23, 2003
PubMed
Summary
This summary is machine-generated.

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DNA array expression profiling began earlier than thought, using radioactive labeling. Technologies evolved, with current trends focusing on data quality, analysis, and hybrid oligonucleotide arrays for research and diagnostics.

Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Expression profiling using DNA arrays is commonly dated to the late 1990s, primarily using non-isotopic methods.
  • Early DNA array technology, starting in 1992 with cDNA arrays, utilized radioactive labeling and evolved from library screening membranes.
  • Simultaneously, oligonucleotide chips, initially for resequencing, were adapted for gene expression measurement.

Observation:

  • Three distinct DNA array approaches (cDNA, oligonucleotide, and later glass microarrays) emerged and continue to coexist.
  • Key advancements include simultaneous measurement of thousands of genes and the development of high-density membranes.
  • The field has seen continuous evolution with a trend towards longer oligonucleotide arrays and improved detection methods.

Findings:

Related Experiment Videos

  • The first cDNA array expression analysis was published in 1992, predating common assumptions and employing radioactive labeling.
  • Multiple array technologies, including cDNA, oligonucleotide chips, and glass microarrays, were developed and co-evolved.
  • Current major issues in DNA array expression profiling involve data quality, analysis, and storage, with a move towards longer oligonucleotide arrays.

Implications:

  • The evolution of DNA arrays offers diverse advantages, driving advancements in both research and diagnostics.
  • Ongoing research focuses on label-free detection methods and novel materials for microarray manufacturing.
  • The field is segmenting into distinct applications: high-throughput diagnostics and high-gene-number research, each with unique requirements.