ImmGen: Gene Expression and Regulation in Immune Cells

免疫基因组计划（ImmGen）是由15个免疫学和 计算生物学实验室，在标准化条件下，对基因进行彻底解剖， 表达及其在小鼠免疫系统中的调节。我们还研究了这些反应如何， 细胞因子和免疫学挑战，免疫基因表达如何与染色质构型相关，以及 使用了最先进的计算算法来推断监管联系。ImmGen数据是公开的 可在专门的网络和智能手机支持，使用交互式图形显示，使结果 对用户来说很直观。这些现在经常被免疫学研究界使用。拟议 继续将利用ImmGen集团的集体专业知识，进一步发展这一重要的公共 resource. (1)扩展和深化纲要，应用单细胞RNAseq非常广泛地定义 在免疫系统中发挥作用的细胞类型，它们的分化轨迹，以及它们对免疫系统的适应 特定的生物体位置这一努力将通过更深层次的细胞类型分析来补充， 鉴定我们将扩大对细胞因子特征的分析，继续绘制非编码RNA（circRNA）， 并追求“开源”计划的协调样本贡献的社区。（二） 免疫基因组学调控网络的机制剖析聚焦于14种细胞类型的核心集 代表了所有主要的免疫谱系。我们将生成高分辨率的转录图谱 通过超深ATACseq绘制因子足迹;通过HiC染色体构象捕获绘制3D架构; 应用ChIPseq来定义增强子和超级增强子、染色质修饰结构域和结构域， 锚;使用机器学习方法将这些互补数据整合到一个全面的 从精细TF足迹到拓扑关联域的监管计划;验证这些 通过与KOMP项目合作，分析核心集转录组和染色质， 在具有转录因子突变的小鼠中， 免疫细胞活性(3)：公开展示。ImmGen数据已成为免疫学中广泛使用的资源 研究，将予以维护和策划。为了实现可扩展性、成本效益， 计算，我们将开发和部署基于云的数据存储和访问解决方案，符合NIH Commons Guidelines.我们将添加到现有的数据行，以允许用户查询 扩展数据（差异表达、调控网络、染色质状态和结构、细胞因子 签名），增加与其他数据源的连接。我们将继续开发流行的移动的应用程序， 并探索这种媒介的特殊用途。ImmGen对免疫学研究产生了积极影响， 本十年，提供详细和严格的免疫群体的基因组解析，由一个 对自身免疫学的深刻理解。这是我们将继续和扩大的。

The Immunological Genome Project (ImmGen) is a collaborative group of 15 Immunology and Computational Biology laboratories who perform, under standardized conditions, a thorough dissection of gene expression and its regulation in the mouse immune system. We also investigated how these respond to cytokines and immunologic challenges, how immune gene expression relates to chromatin configuration, and used cutting-edge computational algorithms to deduce regulatory connections. ImmGen data are publicly available on dedicated web and smartphone supports, using interactive graphic displays that make the results intuitive to users. These are now frequently used by the Immunology research community. The proposed continuation will harness the collective expertise of the ImmGen group to further develop this important public resource. (1) Expand and deepen the compendium, applying single-cell RNAseq to define very broadly the cast of cell-types at play in the immune system, their trajectories of differentiation, and their adaptation to specific organismal locations This effort will be complemented by deeper bulk profiling of cell-types thus identified. We will expand the analysis of cytokine signatures, continue to chart non-coding RNA (circRNAs), and persue the “OpenSource” program of coordinated sample contributions from the community. (2) Mechanistic Dissection of Immunogenomic Regulatory Networks focusing on a Core Set of 14 cell-types that represent all the major immunological lineages. We will generate high-resolution maps of transcription factor footprints by ultra-deep ATACseq; map 3D architectures by HiC chromosome conformation capture; apply ChIPseq to define enhancers and super-enhancers, chromatin modification domains and structural anchors; use machine learning approaches to integrate these complementary data into a comprehensive regulatory plan which spans from fine TF footprints to topologically associated domaiins; validate these inferences by collaborating with the KOMP project to analyze Core Set transcriptomes and chromatin configuration in mice with mutations in transcription factors that determine functionally relevant facets of immunocyte activity. (3): Public Display. ImmGen data have become a widely used resource in Immunology research, which will be maintained and curated. For scalability, cost-effectiveness, and to enable facile computation, we will develop and deploy cloud-based data storage and access solutions, compliant with NIH Commons guidelines. We will add to the existing databrowsers to allow users to query different facets of the expanding data (differential expression, regulatory network, chromatin states and architecture, cytokine signatures), increasing connectivity to other data sources. We will continue developing the popular mobile app, and explore the particular uses of that medium. ImmGen has positively impacted immunological research in the current decade, providing detailed and rigorous genomic resolution of immune populations, informed by a strong understanding of their immunology. This is what we will continue and amplify.