Literature DB >> 20580463

Meta-analysis of lineage-specific gene expression signatures in mouse leukocyte populations.

Neil A Mabbott1, J Kenneth Baillie, David A Hume, Tom C Freeman.   

Abstract

In order to address fundamental questions associated with the relationships between mononuclear phagocytes and other myeloid and lymphoid cell populations, we have taken advantage of the growing body of expression data available in the public domain. We collated a large number of published expression studies on mouse haemopoietic cell lineages comprising 304 cell samples from 29 independent experiments performed on a single microarray platform (Affymetrix MOE430-2). The data were subjected to network-based cluster analysis using Biolayout Express(3D). Genes with related function clustered together in distinct regions of the graph reaffirming many known associations between gene expression and role in specific pathways and defining most major cell types of the immune system. Promoters of genes within individual clusters were distinguished by over-representation of regulatory motifs recognised by specific transcription factors. However, these data indicate that commonly used myeloid subpopulation markers, such as CD11c (Itgax), do not correlate with expression of other genes, and further bring into question their use in defining myeloid cell lineage, activation (M1 vs. M2) and antigen-presenting cell function. In particular, there were few mRNA markers that clearly distinguished classical dendritic cells (DC) from macrophages, other than low expression of genes required for phagocytic activity. Bone marrow-derived DC, grown in GM-CSF, were clearly identified as phagocytes and distinguished from isolated lymphoid tissue DC. Thus, through pooling datasets from public data and examining the gene expression clusters within, we can learn a great deal about the transcriptional networks that underpin the differences in functional activities between cell populations of the immune system. Crown Copyright 2010. Published by Elsevier GmbH. All rights reserved.

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Year:  2010        PMID: 20580463     DOI: 10.1016/j.imbio.2010.05.012

Source DB:  PubMed          Journal:  Immunobiology        ISSN: 0171-2985            Impact factor:   3.144


  48 in total

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