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Identification of Co-expressed Gene Signatures in Mouse B1, Marginal Zone and B2 B-cell Populations

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)79-95
JournalImmunology
Volume141
Issue number1
Early online date12 Sep 2013
DOIs
Publication statusPublished - 1 Jan 2014

Abstract

In mice three major B-cell subsets have been identified with distinct functionalities: B1 B cells, marginal zone B cells and follicular B2 B cells. Here, we utilized the growing body of publicly available transcriptomics data to create an expression atlas of 84 gene expression microarray data sets of distinct mouse B-cell subsets. These data were subjected to network-based cluster analysis using BioLayout Express(3D) . Using this analysis tool, genes with related function clustered together in discrete regions of the network graph and enabled the identification of transcriptional networks that underpinned the functional activity of distinct cell populations. Some gene clusters were expressed highly by most of the cell populations included in this analysis (such as those with activity related to house-keeping functions). Others contained genes with expression patterns specific to distinct B-cell subsets. While these clusters contained many genes typically associated with the activity of the cells they were specifically expressed in, many novel B-cell-subset specific candidate genes were identified. A large number of uncharacterized genes were also represented in these B-cell lineage-specific clusters. Further analysis of the activities of these uncharacterized candidate genes will lead to the identification of novel B-cell lineage-specific transcription factors and regulators of B-cell function. We also analysed 36 microarray data sets from distinct human B-cell populations. These data showed that mouse and human GC B cells shared similar transcriptional features, whereas mouse B1 B cells were distinct from proposed human B1 B cells. This article is protected by copyright. All rights reserved.

    Research areas

  • B cells, meta-analysis, microarray, transcriptomics

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