Literature DB >> 19233957

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

Douwe van der Veen1, José Miguel Oliveira, Willy A M van den Berg, Leo H de Graaff.   

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.

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Year:  2009        PMID: 19233957      PMCID: PMC2675206          DOI: 10.1128/AEM.02270-08

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  33 in total

1.  Characterization of SYBR Gold nucleic acid gel stain: a dye optimized for use with 300-nm ultraviolet transilluminators.

Authors:  R S Tuma; M P Beaudet; X Jin; L J Jones; C Y Cheung; S Yue; V L Singer
Journal:  Anal Biochem       Date:  1999-03-15       Impact factor: 3.365

2.  Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Authors:  A Brazma; P Hingamp; J Quackenbush; G Sherlock; P Spellman; C Stoeckert; J Aach; W Ansorge; C A Ball; H C Causton; T Gaasterland; P Glenisson; F C Holstege; I F Kim; V Markowitz; J C Matese; H Parkinson; A Robinson; U Sarkans; S Schulze-Kremer; J Stewart; R Taylor; J Vilo; M Vingron
Journal:  Nat Genet       Date:  2001-12       Impact factor: 38.330

Review 3.  Design issues for cDNA microarray experiments.

Authors:  Yee Hwa Yang; Terry Speed
Journal:  Nat Rev Genet       Date:  2002-08       Impact factor: 53.242

4.  The genetics of Aspergillus nidulans.

Authors:  G PONTECORVO; J A ROPER; L M HEMMONS; K D MACDONALD; A W J BUFTON
Journal:  Adv Genet       Date:  1953       Impact factor: 1.944

Review 5.  Performing quantitative reverse-transcribed polymerase chain reaction experiments.

Authors:  Georges Lutfalla; Gilles Uze
Journal:  Methods Enzymol       Date:  2006       Impact factor: 1.600

6.  The fission yeast dma1 gene is a component of the spindle assembly checkpoint, required to prevent septum formation and premature exit from mitosis if spindle function is compromised.

Authors:  M Murone; V Simanis
Journal:  EMBO J       Date:  1996-12-02       Impact factor: 11.598

7.  beta-Xylosidase activity, encoded by xlnD, is essential for complete hydrolysis of xylan by Aspergillus niger but not for induction of the xylanolytic enzyme spectrum.

Authors:  N N van Peij; J Brinkmann; M Vrsanská; J Visser; L H de Graaff
Journal:  Eur J Biochem       Date:  1997-04-01

8.  Comparison of mRNA gene expression by RT-PCR and DNA microarray.

Authors:  Wiguins Etienne; Martha H Meyer; Johnny Peppers; Ralph A Meyer
Journal:  Biotechniques       Date:  2004-04       Impact factor: 1.993

Review 9.  An assessment of recently published gene expression data analyses: reporting experimental design and statistical factors.

Authors:  Peyman Jafari; Francisco Azuaje
Journal:  BMC Med Inform Decis Mak       Date:  2006-06-21       Impact factor: 2.796

10.  Microarray validation: factors influencing correlation between oligonucleotide microarrays and real-time PCR.

Authors:  Jeanine S Morey; James C Ryan; Frances M Van Dolah
Journal:  Biol Proced Online       Date:  2006-12-12       Impact factor: 3.244

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  16 in total

1.  Shotgun proteomics of Aspergillus niger microsomes upon D-xylose induction.

Authors:  José Miguel P Ferreira de Oliveira; Mark W J van Passel; Peter J Schaap; Leo H de Graaff
Journal:  Appl Environ Microbiol       Date:  2010-05-07       Impact factor: 4.792

2.  Dual transcriptional profiling of a bacterial/fungal confrontation: Collimonas fungivorans versus Aspergillus niger.

Authors:  Francesca Mela; Kathrin Fritsche; Wietse de Boer; Johannes A van Veen; Leo H de Graaff; Marlies van den Berg; Johan H J Leveau
Journal:  ISME J       Date:  2011-05-26       Impact factor: 10.302

3.  d-Xylose concentration-dependent hydrolase expression profiles and the function of CreA and XlnR in Aspergillus niger.

Authors:  Astrid R Mach-Aigner; Jimmy Omony; Birgit Jovanovic; Anton J B van Boxtel; Leo H de Graaff
Journal:  Appl Environ Microbiol       Date:  2012-02-17       Impact factor: 4.792

4.  Modeling and analysis of the dynamic behavior of the XlnR regulon in Aspergillus niger.

Authors:  Jimmy Omony; Leo H de Graaff; Gerrit van Straten; Anton J B van Boxtel
Journal:  BMC Syst Biol       Date:  2011-06-20

5.  Biocatalytic potential of laccase-like multicopper oxidases from Aspergillus niger.

Authors:  Juan Antonio Tamayo-Ramos; Willem J H van Berkel; Leo H de Graaff
Journal:  Microb Cell Fact       Date:  2012-12-27       Impact factor: 5.328

6.  Proteomic analysis of the secretory response of Aspergillus niger to D-maltose and D-xylose.

Authors:  José Miguel P Ferreira de Oliveira; Mark W J van Passel; Peter J Schaap; Leo H de Graaff
Journal:  PLoS One       Date:  2011-06-17       Impact factor: 3.240

7.  An inventory of the Aspergillus niger secretome by combining in silico predictions with shotgun proteomics data.

Authors:  Machtelt Braaksma; Elena S Martens-Uzunova; Peter J Punt; Peter J Schaap
Journal:  BMC Genomics       Date:  2010-10-19       Impact factor: 3.969

8.  Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments.

Authors:  Robert R Kitchen; Vicky S Sabine; Arthur A Simen; J Michael Dixon; John M S Bartlett; Andrew H Sims
Journal:  BMC Genomics       Date:  2011-12-01       Impact factor: 3.969

9.  The Aspergillus niger multicopper oxidase family: analysis and overexpression of laccase-like encoding genes.

Authors:  Juan A Tamayo Ramos; Sharief Barends; Raymond M D Verhaert; Leo H de Graaff
Journal:  Microb Cell Fact       Date:  2011-10-08       Impact factor: 5.328

10.  Expression of the Aspergillus terreus itaconic acid biosynthesis cluster in Aspergillus niger.

Authors:  Laura van der Straat; Marloes Vernooij; Marieke Lammers; Willy van den Berg; Tom Schonewille; Jan Cordewener; Ingrid van der Meer; Andries Koops; Leo H de Graaff
Journal:  Microb Cell Fact       Date:  2014-01-17       Impact factor: 5.328

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