Open AccessAnalysis of Variance Components Reveals the Contribution of Sample Processing to Transcript Variation
Author(s) -
Douwe van der Veen,
José Miguel Oliveira,
W.A.M. van den Berg,
L.H. de Graaff
Publication year - 2009
Publication title -
applied and environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.552
H-Index - 324
eISSN - 1070-6291
pISSN - 0099-2240
DOI - 10.1128/aem.02270-08
Subject(s) - dna microarray , xylose , biology , computational biology , replicate , microarray , biological system , microarray analysis techniques , genetics , gene , gene expression , biochemistry , fermentation , mathematics , statistics
The proper design of DNA microarray experiments requires knowledge of biological and technical variation of the studied biological model. For the filamentous fungusAspergillus 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 tod -xylose was analyzed using Affymetrix microarrays. Twenty-four statistically differentially expressed genes were identified. These encode enzymes required to degrade and metabolized -xylose-containing polysaccharides, as well as complementary enzymes required to metabolize complex polymers likely present in the vicinity ofd -xylose-containing substrates. These results confirm previous findings that thed -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.