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小鼠白细胞群体谱系特异性基因表达特征的荟萃分析。

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

机构信息

The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Roslin Biocentre, Roslin, Midlothian, UK.

出版信息

Immunobiology. 2010 Sep-Oct;215(9-10):724-36. doi: 10.1016/j.imbio.2010.05.012. Epub 2010 Jun 4.

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.

摘要

为了解决与单核吞噬细胞和其他髓系和淋巴样细胞群体之间关系相关的基本问题,我们利用了公共领域中日益增长的表达数据。我们整理了大量关于小鼠造血细胞谱系的已发表表达研究,这些研究包括 29 个独立实验在单个微阵列平台(Affymetrix MOE430-2)上获得的 304 个细胞样本。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,这再次证实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控基序的过度表达来区分。然而,这些数据表明,常用的髓样亚群标记物,如 CD11c(Itgax),与其他基因的表达不相关,进一步质疑了它们在定义髓样细胞谱系、激活(M1 与 M2)和抗原呈递细胞功能中的用途。特别是,除了吞噬活性所需基因的低表达外,很少有 mRNA 标记物可以清楚地区分经典树突状细胞(DC)和巨噬细胞。在 GM-CSF 中生长的骨髓来源的 DC 被明确鉴定为吞噬细胞,并与分离的淋巴组织 DC 区分开来。因此,通过汇集公共数据集中的数据并检查其中的基因表达簇,我们可以了解很多关于免疫系统细胞群体之间功能活性差异的转录网络。

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