Literature DB >> 16970301

Automated target preparation for microarray-based gene expression analysis.

Frédéric Raymond1, Sylviane Metairon, Roland Borner, Markus Hofmann, Martin Kussmann.   

Abstract

DNA microarrays have rapidly evolved toward a platform for massively paralleled gene expression analysis. Despite its widespread use, the technology has been criticized to be vulnerable to technical variability. Addressing this issue, recent comparative, interplatform, and interlaboratory studies have revealed that, given defined procedures for "wet lab" experiments and data processing, a satisfactory reproducibility and little experimental variability can be achieved. In view of these advances in standardization, the requirement for uniform sample preparation becomes evident, especially if a microarray platform is used as a facility, i.e., by different users working in the laboratory. While one option to reduce technical variability is to dedicate one laboratory technician to all microarray studies, we have decided to automate the entire RNA sample preparation implementing a liquid handling system coupled to a thermocycler and a microtiter plate reader. Indeed, automated RNA sample preparation prior to chip analysis enables (1) the reduction of experimentally caused result variability, (2) the separation of (important) biological variability from (undesired) experimental variation, and (3) interstudy comparison of gene expression results. Our robotic platform can process up to 24 samples in parallel, using an automated sample preparation method that produces high-quality biotin-labeled cRNA ready to be hybridized on Affymetrix GeneChips. The results show that the technical interexperiment variation is less pronounced than with manually prepared samples. Moreover, experiments using the same starting material showed that the automated process yields a good reproducibility between samples.

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Year:  2006        PMID: 16970301     DOI: 10.1021/ac060097t

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  5 in total

1.  Six weeks' sebacic acid supplementation improves fasting plasma glucose, HbA1c and glucose tolerance in db/db mice.

Authors:  M Membrez; C J Chou; F Raymond; R Mansourian; M Moser; I Monnard; C Ammon-Zufferey; K Mace; G Mingrone; C Binnert
Journal:  Diabetes Obes Metab       Date:  2010-12       Impact factor: 6.577

2.  Comparative gene expression profiling between human cultured myotubes and skeletal muscle tissue.

Authors:  Frederic Raymond; Sylviane Métairon; Martin Kussmann; Jaume Colomer; Andres Nascimento; Emma Mormeneo; Cèlia García-Martínez; Anna M Gómez-Foix
Journal:  BMC Genomics       Date:  2010-02-22       Impact factor: 3.969

3.  Transcriptomic analysis comparing tumor-associated neutrophils with granulocytic myeloid-derived suppressor cells and normal neutrophils.

Authors:  Zvi G Fridlender; Jing Sun; Inbal Mishalian; Sunil Singhal; Guanjun Cheng; Veena Kapoor; Wenhwai Horng; Gil Fridlender; Rachel Bayuh; G Scott Worthen; Steven M Albelda
Journal:  PLoS One       Date:  2012-02-14       Impact factor: 3.240

4.  Lactoferrin Promotes Early Neurodevelopment and Cognition in Postnatal Piglets by Upregulating the BDNF Signaling Pathway and Polysialylation.

Authors:  Yue Chen; Zhiqiang Zheng; Xi Zhu; Yujie Shi; Dandan Tian; Fengjuan Zhao; Ni Liu; Petra S Hüppi; Frederic A Troy; Bing Wang
Journal:  Mol Neurobiol       Date:  2014-08-23       Impact factor: 5.590

5.  Automation of cDNA synthesis and labelling improves reproducibility.

Authors:  Daniel Klevebring; Marcus Gry; Johan Lindberg; Anna Eidefors; Joakim Lundeberg
Journal:  J Biomed Biotechnol       Date:  2009-10-15
  5 in total

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