Literature DB >> 16645204

In vitro transcription amplification and labeling methods contribute to the variability of gene expression profiling with DNA microarrays.

Changqing Ma1, Maureen Lyons-Weiler, Wenjing Liang, William LaFramboise, John R Gilbertson, Michael J Becich, Federico A Monzon.   

Abstract

The effect of different amplification and labeling methods on DNA microarray expression results has not been previously delineated. To analyze the variation associated with widely accepted T7-based RNA amplificationand labeling methods, aliquots of the Stratagene Human Universal Reference RNA were labeled using three eukaryotic target preparation methods followed by uniform replicate array hybridization (Affymetrix U95Av2). Method-dependent variability was observed in the yield and size distribution of labeled products, as well as in the gene expression results. A significant increase in short transcripts, when compared to unamplified mRNA, was observed in methods with long in vitro transcription reactions. Intramethod reproducibility showed correlation coefficients >0.99, whereas intermethod comparisons showed coefficients ranging from 0.94 to 0.98 and a nearly twofold increase in coefficient of variation. Fold amplification for each method positively correlated with the number of genes present. Our experiments uncovered two factors that introduced significant bias in gene expression data: the number of labeled nucleotides, which introduces sequence-dependent bias, and the length of the in vitro transcription reaction, which introduces transcript size-dependent bias. This study provides evidence that variability in expression data may be caused, in part, by differences in amplification and labeling protocols.

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Year:  2006        PMID: 16645204      PMCID: PMC1867595          DOI: 10.2353/jmoldx.2006.050077

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  25 in total

1.  Quantitative analysis of mRNA amplification by in vitro transcription.

Authors:  L R Baugh; A A Hill; E L Brown; C P Hunter
Journal:  Nucleic Acids Res       Date:  2001-03-01       Impact factor: 16.971

2.  A highly reproducible, linear, and automated sample preparation method for DNA microarrays.

Authors:  David R Dorris; Ramesh Ramakrishnan; Dionisios Trakas; Frank Dudzik; Richard Belval; Connie Zhao; Allen Nguyen; Marc Domanus; Abhijit Mazumder
Journal:  Genome Res       Date:  2002-06       Impact factor: 9.043

3.  QA/QC as a pressing need for microarray analysis: meeting report from CAMDA'02.

Authors:  Kim Johnson; Simon Lin
Journal:  Biotechniques       Date:  2003-03       Impact factor: 1.993

4.  Amplified RNA synthesized from limited quantities of heterogeneous cDNA.

Authors:  R N Van Gelder; M E von Zastrow; A Yool; W C Dement; J D Barchas; J H Eberwine
Journal:  Proc Natl Acad Sci U S A       Date:  1990-03       Impact factor: 11.205

5.  Cluster analysis and display of genome-wide expression patterns.

Authors:  M B Eisen; P T Spellman; P O Brown; D Botstein
Journal:  Proc Natl Acad Sci U S A       Date:  1998-12-08       Impact factor: 11.205

6.  Evaluation of a linear amplification method for small samples used on high-density oligonucleotide microarray analysis.

Authors:  Catherine I Dumur; Carleton T Garrett; Kellie J Archer; Suhail Nasim; David S Wilkinson; Andrea Ferreira-Gonzalez
Journal:  Anal Biochem       Date:  2004-08-15       Impact factor: 3.365

7.  Gene expression profiling identifies clinically relevant subtypes of prostate cancer.

Authors:  Jacques Lapointe; Chunde Li; John P Higgins; Matt van de Rijn; Eric Bair; Kelli Montgomery; Michelle Ferrari; Lars Egevad; Walter Rayford; Ulf Bergerheim; Peter Ekman; Angelo M DeMarzo; Robert Tibshirani; David Botstein; Patrick O Brown; James D Brooks; Jonathan R Pollack
Journal:  Proc Natl Acad Sci U S A       Date:  2004-01-07       Impact factor: 11.205

8.  Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.

Authors:  C Li; W H Wong
Journal:  Proc Natl Acad Sci U S A       Date:  2001-01-02       Impact factor: 11.205

9.  Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application.

Authors:  C Li; W Hung Wong
Journal:  Genome Biol       Date:  2001-08-03       Impact factor: 13.583

10.  Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis.

Authors:  Hongjuan Zhao; Trevor Hastie; Michael L Whitfield; Anne-Lise Børresen-Dale; Stefanie S Jeffrey
Journal:  BMC Genomics       Date:  2002-10-30       Impact factor: 3.969

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  12 in total

1.  Influence of RNA labeling on expression profiling of microRNAs.

Authors:  John S Kaddis; Daniel H Wai; Jessica Bowers; Nicole Hartmann; Lukas Baeriswyl; Sheetal Bajaj; Michael J Anderson; Robert C Getts; Timothy J Triche
Journal:  J Mol Diagn       Date:  2011-11-07       Impact factor: 5.568

Review 2.  Quality assurance of RNA expression profiling in clinical laboratories.

Authors:  Weihua Tang; Zhiyuan Hu; Hind Muallem; Margaret L Gulley
Journal:  J Mol Diagn       Date:  2011-10-20       Impact factor: 5.568

3.  Development of the "Three-step MACS": a novel strategy for isolating rare cell populations in the absence of known cell surface markers from complex animal tissue.

Authors:  Mathia Y Lee; Thomas Lufkin
Journal:  J Biomol Tech       Date:  2012-07

4.  Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

Authors:  Uma R Chandran; Changqing Ma; Rajiv Dhir; Michelle Bisceglia; Maureen Lyons-Weiler; Wenjing Liang; George Michalopoulos; Michael Becich; Federico A Monzon
Journal:  BMC Cancer       Date:  2007-04-12       Impact factor: 4.430

5.  A novel approach for reliable microarray analysis of microdissected tumor cells from formalin-fixed and paraffin-embedded colorectal cancer resection specimens.

Authors:  Silke Lassmann; Clemens Kreutz; Anja Schoepflin; Ulrich Hopt; Jens Timmer; Martin Werner
Journal:  J Mol Med (Berl)       Date:  2008-12-06       Impact factor: 4.599

6.  Interlaboratory performance of a microarray-based gene expression test to determine tissue of origin in poorly differentiated and undifferentiated cancers.

Authors:  Catherine I Dumur; Maureen Lyons-Weiler; Christin Sciulli; Carleton T Garrett; Iris Schrijver; Tara K Holley; Juan Rodriguez-Paris; Jonathan R Pollack; James L Zehnder; Melissa Price; Jill M Hagenkord; C Ted Rigl; Ljubomir J Buturovic; Glenda G Anderson; Federico A Monzon
Journal:  J Mol Diagn       Date:  2007-12-13       Impact factor: 5.568

7.  AffyRNADegradation: control and correction of RNA quality effects in GeneChip expression data.

Authors:  Mario Fasold; Hans Binder
Journal:  Bioinformatics       Date:  2012-10-24       Impact factor: 6.937

8.  An adaptable method using human mixed tissue ratiometric controls for benchmarking performance on gene expression microarrays in clinical laboratories.

Authors:  P Scott Pine; Barry A Rosenzweig; Karol L Thompson
Journal:  BMC Biotechnol       Date:  2011-04-12       Impact factor: 2.563

9.  Motif composition, conservation and condition-specificity of single and alternative transcription start sites in the Drosophila genome.

Authors:  Elizabeth A Rach; Hsiang-Yu Yuan; William H Majoros; Pavel Tomancak; Uwe Ohler
Journal:  Genome Biol       Date:  2009-07-09       Impact factor: 13.583

10.  Estimating RNA-quality using GeneChip microarrays.

Authors:  Mario Fasold; Hans Binder
Journal:  BMC Genomics       Date:  2012-05-14       Impact factor: 3.969

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