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A rapid method for computationally inferring transcriptome coverage and microarray sensitivity.

A Reverter1, S M McWilliam, W Barris

  • 1Bioinformatics Group, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia. Tony.Reverter-Gomez@csiro.au

Bioinformatics (Oxford, England)
|August 17, 2004
PubMed
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Approximately 340,000 sequences are sufficient for microarray gene expression analysis. However, this number is inadequate for tag-based technologies, which require genome sequencing for full transcript identification.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Diverse gene expression technologies exist, including microarrays and tag-based methods like SAGE and MPSS.
  • Transcriptome and genome coverage varies across organisms, impacting technology performance.
  • Assessing required coverage levels and technology sensitivity is crucial for experimental design.

Purpose of the Study:

  • To determine the necessary transcriptome coverage for different gene expression technologies.
  • To evaluate the sensitivity of various experimental approaches.
  • To compare the efficiency of microarrays versus tag-based methods regarding sequence coverage.

Main Methods:

  • Transcriptome coverage was estimated using random sampling against a tag-to-gene mapping.

Related Experiment Videos

  • Microarray intensity thresholds were used to define transcript abundance distributions.
  • Sensitivity was calculated by comparing intensity distributions of all transcripts versus differentially expressed genes.

    • Main Results:

    • A collection of ~340,000 sequences provides adequate coverage for microarrays.
    • This sequence count is insufficient for optimal utilization of tag-based gene expression technologies.
    • Without large-scale sequencing, many tags from these methods remain unidentifiable.

    Conclusions:

    • Microarray sensitivity is achievable with moderate sequence coverage.
    • Tag-based technologies necessitate higher sequence coverage, ideally linked to genome sequencing, for full transcript identification.
    • The choice of gene expression technology should align with available sequencing resources and organism-specific genomic data.