Monocytes and macrophages differentiate from progenitor cells under the influence of colony-stimulating factors. Genome-scale data have enabled the identification of the sets of genes that are associated with specific functions and the mechanisms by which thousands of genes are regulated in response to pathogen challenge. In large datasets, it is possible to identify large sets of genes that are coregulated with the transcription factors that regulate them. They include macrophage-specific genes, interferon-responsive genes, early inflammatory genes, and those associated with endocytosis. Such analyses can also extract macrophage-associated signatures from large cancer tissue datasets. However, cluster analysis provides no support for a signature that distinguishes macrophages from antigen-presenting dendritic cells, nor the classification of macrophage activation states as classical versus alternative, or M1 versus M2. Although there has been a focus on a small subset of lineage-enriched transcription factors, such as PU.1, more than half of the transcription factors in the genome can be expressed in macrophage lineage cells under some state of activation, and they interact in a complex network. The network architecture is conserved across species, but many of the target genes evolve rapidly and differ between mouse and human. The data and publication deluge related to macrophage biology require the development of new analytical tools and ways of presenting information in an accessible form.

中文翻译：

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单核吞噬细胞分化和活化的转录组学分析。

单核细胞和巨噬细胞在集落刺激因子的影响下从祖细胞分化。基因组规模的数据能够识别与特定功能相关的基因组以及数千个基因在应对病原体挑战时受到调节的机制。在大型数据集中，可以识别与调节它们的转录因子共同调节的大量基因。它们包括巨噬细胞特异性基因、干扰素反应基因、早期炎症基因和与内吞作用相关的基因。这种分析还可以从大型癌症组织数据集中提取巨噬细胞相关特征。然而，聚类分析不支持区分巨噬细胞与抗原呈递树突细胞的特征，也没有将巨噬细胞激活状态分类为经典与替代，或 M1 与 M2。尽管一直关注一小部分富含谱系的转录因子，例如 PU.1，但基因组中超过一半的转录因子可以在某些激活状态下在巨噬细胞谱系细胞中表达，并且它们在一个复杂的网络。网络结构在物种间是保守的，但许多靶基因进化迅速，并且在小鼠和人类之间存在差异。与巨噬细胞生物学相关的数据和出版物泛滥需要开发新的分析工具和以可访问的形式呈现信息的方法。如PU.1，基因组中一半以上的转录因子在某种激活状态下可以在巨噬细胞谱系细胞中表达，它们以复杂的网络相互作用。网络结构在物种间是保守的，但许多靶基因进化迅速，并且在小鼠和人类之间存在差异。与巨噬细胞生物学相关的数据和出版物泛滥需要开发新的分析工具和以可访问的形式呈现信息的方法。如PU.1，基因组中一半以上的转录因子在某种激活状态下可以在巨噬细胞谱系细胞中表达，它们以复杂的网络相互作用。网络结构在物种间是保守的，但许多靶基因进化迅速，并且在小鼠和人类之间存在差异。与巨噬细胞生物学相关的数据和出版物泛滥需要开发新的分析工具和以可访问的形式呈现信息的方法。