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Open Access Methodology article

Design and evaluation of Actichip, a thematic microarray for the study of the actin cytoskeleton

Jean Muller124, André Mehlen1, Guillaume Vetter13, Mikalai Yatskou1, Arnaud Muller1, Frédéric Chalmel25, Olivier Poch2, Evelyne Friederich13 and Laurent Vallar1*

Author Affiliations

1 Laboratoire de Biologie Moléculaire, d'Analyse Génique et de Modélisation, Centre de Recherche Public-Santé, 84 rue Val Fleuri, L-1526 Luxembourg, Luxembourg

2 Laboratoire de Bioinformatique et Génomique Intégratives, Institut de Génétique et de Biologie Moléculaire et Cellulaire; Inserm, U596; CNRS, UMR7104, F-67400 Illkirch, Université Louis Pasteur, F-67000 Strasbourg, France

3 Cytoskeleton and cell plasticity laboratory, Life Sciences RU, University of Luxembourg, 162a Avenue de la faïencerie, L-1511 Luxembourg, Luxembourg

4 Computational Biology Unit, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany

5 GERHM-Inserm U625, Université Rennes I, Campus de Beaulieu, Bt 13, Avenue du Général Leclerc, F-35042 Rennes cedex, France

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BMC Genomics 2007, 8:294  doi:10.1186/1471-2164-8-294

Published: 29 August 2007

Abstract

Background

The actin cytoskeleton plays a crucial role in supporting and regulating numerous cellular processes. Mutations or alterations in the expression levels affecting the actin cytoskeleton system or related regulatory mechanisms are often associated with complex diseases such as cancer. Understanding how qualitative or quantitative changes in expression of the set of actin cytoskeleton genes are integrated to control actin dynamics and organisation is currently a challenge and should provide insights in identifying potential targets for drug discovery. Here we report the development of a dedicated microarray, the Actichip, containing 60-mer oligonucleotide probes for 327 genes selected for transcriptome analysis of the human actin cytoskeleton.

Results

Genomic data and sequence analysis features were retrieved from GenBank and stored in an integrative database called Actinome. From these data, probes were designed using a home-made program (CADO4MI) allowing sequence refinement and improved probe specificity by combining the complementary information recovered from the UniGene and RefSeq databases. Actichip performance was analysed by hybridisation with RNAs extracted from epithelial MCF-7 cells and human skeletal muscle. Using thoroughly standardised procedures, we obtained microarray images with excellent quality resulting in high data reproducibility. Actichip displayed a large dynamic range extending over three logs with a limit of sensitivity between one and ten copies of transcript per cell. The array allowed accurate detection of small changes in gene expression and reliable classification of samples based on the expression profiles of tissue-specific genes. When compared to two other oligonucleotide microarray platforms, Actichip showed similar sensitivity and concordant expression ratios. Moreover, Actichip was able to discriminate the highly similar actin isoforms whereas the two other platforms did not.

Conclusion

Our data demonstrate that Actichip is a powerful alternative to commercial high density microarrays for cytoskeleton gene profiling in normal or pathological samples. Actichip is available upon request.