Meta-analysis of lineage-specific gene expression signatures in mouse leukocyte populations
Meta-analysis of lineage-specific gene expression signatures in mouse leukocyte populations
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DOI：
10.1016/j.imbio.2010.05.012
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发表时间：
2010-09-01
期刊：
影响因子：
2.8
通讯作者：
Freeman, Tom C.
中科院分区：
文献类型：
--
作者：
Mabbott, Neil A.;Baillie, J. Kenneth;Freeman, Tom C.
为了解决与单核吞噬细胞和其他骨髓和淋巴细胞群体之间的关系相关的基本问题，我们利用了公共领域中越来越多的表达数据。我们整理了大量已发表的关于小鼠造血细胞谱系的表达研究，这些研究包括来自在单个微阵列平台（Affytek MOE 430 -2）上进行的29个独立实验的304个细胞样品。使用Biolayout Express（3D）对数据进行基于网络的聚类分析。具有相关功能的基因在图的不同区域聚集在一起，重申了基因表达与特定途径中的作用之间的许多已知关联，并定义了免疫系统的大多数主要细胞类型。单个簇内基因的启动子通过特定转录因子识别的调节基序的过度表达来区分。然而，这些数据表明，常用的髓系亚群标记物，如CD 11 c（Itgax），与其他基因的表达不相关，并进一步提出了问题，他们在定义髓系细胞谱系，活化（M1与M2）和抗原呈递细胞功能的使用。特别是，除了吞噬活性所需基因的低表达外，几乎没有mRNA标记物可以清楚地区分经典树突状细胞（DC）和巨噬细胞。骨髓来源的DC，生长在GM-CSF中，被清楚地鉴定为吞噬细胞，并与分离的淋巴组织DC区分开来。因此，通过汇集来自公共数据的数据集并检查其中的基因表达簇，我们可以了解大量关于转录网络的信息，这些网络是免疫系统细胞群之间功能活动差异的基础。Crown版权所有（C）2010由Elsevier GmbH发布。All rights reserved.
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 (C) 2010 Published by Elsevier GmbH. All rights reserved.