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Analysis of variance components reveals the contribution of sample processing to transcript variation

  • D. van der Veen
  • , J.M. Oliveira
  • , W.A.M. van den Berg
  • , L.H. de Graaff

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

The proper design of DNA microarray experiments requires knowledge of biological and technical variation of the studied biological model. For the filamentous fungus Aspergillus niger, a fast, quantitative real-time PCR (qPCR)-based hierarchical experimental design was used to determine this variation. Analysis of variance components determined the contribution of each processing step to total variation: 68% is due to differences in day-to-day handling and processing, while the fermentor vessel, cDNA synthesis, and qPCR measurement each contributed equally to the remainder of variation. The global transcriptional response to d-xylose was analyzed using Affymetrix microarrays. Twenty-four statistically differentially expressed genes were identified. These encode enzymes required to degrade and metabolize D-xylose-containing polysaccharides, as well as complementary enzymes required to metabolize complex polymers likely present in the vicinity of D-xylose-containing substrates. These results confirm previous findings that the d-xylose signal is interpreted by the fungus as the availability of a multitude of complex polysaccharides. Measurement of a limited number of transcripts in a defined experimental setup followed by analysis of variance components is a fast and reliable method to determine biological and technical variation present in qPCR and microarray studies. This approach provides important parameters for the experimental design of batch-grown filamentous cultures and facilitates the evaluation and interpretation of microarray data
Original languageEnglish
Pages (from-to)2414-2422
JournalApplied and Environmental Microbiology
Volume75
Issue number8
DOIs
Publication statusPublished - 2009

Keywords

  • time rt-pcr
  • aspergillus-niger
  • gene-expression
  • microarray experiments
  • quantification
  • information
  • standards
  • nidulans
  • cloning
  • growth

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