Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer. Gene expression architecture of mouse dorsal and tail skin reveals functional differences in inflammation and cancer

Gene expression levels in normal tissues can differ substantially between individuals, due to inherited polymorphisms acting in cis or trans. Analysis of this variation across a population of genetically distinct individuals allows us to visualize a network of co-expressed genes under normal homeostatic conditions, and the consequences of perturbation by tissue damage or disease development. Here, we explore gene expression networks in normal adult skin from 470 genetically unique mice, and demonstrate the dependence of the architecture of signaling pathways on skin tissue location (dorsal or tail skin) and perturbation by induction of inflammation or tumorigenesis. Gene networks related to specific cell types, as well as signaling pathways including Sonic Hedgehog (Shh), Wnt, Lgr family stem cell markers, and keratins differed at these tissue sites, suggesting mechanisms for the differential susceptibility of dorsal and tail skin to development of skin diseases and tumorigenesis. The Pten tumor suppressor gene network is extensively rewired in premalignant tumors compared to normal tissue, but this response to perturbation is lost during malignant progression. We present a software package for eQTL network analysis and demonstrate how network analysis of whole tissues provides insights into interactions between cell compartments and signaling molecules. Overall design: Refer to individual Series

正常组织的基因表达水平在个体间存在显著差异，这源于顺式（cis）或反式（trans）作用的遗传多态性。对遗传背景各异的个体群体中的此类表达差异进行分析，可帮助我们构建正常稳态条件下的共表达基因网络可视化图谱，并解析组织损伤或疾病发生所引发的扰动效应。
本研究针对470只遗传背景独特的正常成年小鼠皮肤开展基因表达网络分析，阐明了信号通路架构如何依赖于皮肤组织位置（背部皮肤或尾部皮肤），以及炎症诱导或肿瘤发生所引发的扰动效应。
与特定细胞类型相关的基因网络，以及包括音猬因子（Sonic Hedgehog, Shh）、Wnt、Lgr家族干细胞标志物及角蛋白在内的信号通路，在两类皮肤组织中存在显著差异，这为背部与尾部皮肤对皮肤疾病及肿瘤发生的易感性差异提供了潜在机制解释。
与正常组织相比，癌前肿瘤中的磷酸酶与张力蛋白同源物（Phosphatase and tensin homolog, Pten）抑癌基因网络发生了广泛重连，但在恶性进展过程中，这种对扰动的应答会消失。
我们开发了一款用于表达数量性状位点（expression quantitative trait locus, eQTL）网络分析的软件包，并验证了全组织网络分析如何为解析细胞区室与信号分子间的相互作用提供新视角。
实验整体设计：详见各独立数据集系列。