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Bioinformatic Analysis of Expression Data of ApoE Deficient Mice
Olga Papadodima1, Allan Sirsjo2, and Aristotelis Chatziioanou1
1Institute of Biological Research and Biotechnology, National Hellenic Research Foundation, 48 Vas. Constantinou Ave., 11635, Athens, Greece
2School of Health and Medical Sciences, Division of Clinical Medicine, University of Örebro, Sweden
Abstract. Atherosclerosis is a multifactorial disease involving a lot of genes and proteins recruited throughout its manifestation. The present study aims to exploit bioinformatic tools in order to analyze microarray data of atherosclerotic aortic lesions of ApoE knockout mice, a model widely used in atherosclerosis research. In particular, a dynamic analysis was performed among young and aged animals, resulting in a list of 852 significantly altered genes. Pathway analysis indicated alterations in critical cellular processes related to cell communication and signal transduction, immune response, lipid transport and metabolism. Cluster analysis partitioned the significantly differentiated genes in three major clusters of similar expression profile. Promoter analysis applied to functional related groups of the same cluster, revealed shared putative cis-elements potentially contributing to a common regulatory mechanism. Finally, by reverse engineering the functional relevance of differentially expressed genes with specific cellular pathways, putative genes acting as hubs were identified, linking functionally disparate cellular processes in the context of traditional molecular description.
Keywords: Microarray analysis, Atherosclerosis, transcriptomic analysis, promoter analysis
LNAI 7297, p. 254 ff.
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© Springer-Verlag Berlin Heidelberg 2012