Data Analysis Core

项目总结 数据分析核心将通过计算定义和表征转录和表观基因组签名 小鼠脑、骨髓、结肠、乳腺和肝脏细胞类型的细胞衰老研究 雌性幼鼠和老年鼠。我们将使用已建立的可伸缩管道来处理 生物分析核心，创建脑、骨髓、结肠、乳房和肝脏细胞类型的综合图谱 同时使用从所有单细胞测序和成像分析中获得的细胞图谱。使用此集成 图中，我们将基于基因识别每种组织驻留细胞类型中的衰老细胞群 已知的细胞衰老标志物的表达和表观基因组图谱，并定义了两个异质性亚群 衰老细胞的类型以及具有非规范轮廓的“衰老样”细胞。对于每个年老的人和 我们将定义其顺式调节方案，包括候选顺式调节元件 (CCRE)、染色质状态、转录调节因子和CCRE活性的靶基因(即基因增强子- 启动子网络)，以及它们的空间定位和微环境。我们将描述以下方面的变化 衰老和衰老样细胞亚型以及细胞类型的丰度和顺式调节 整个生命周期的衰老生态位与性别、细胞类型和组织区域有关。这个整合的转录本 衰老细胞的表观基因组图谱将比单纯的转录组更好地定义和解析衰老细胞。 我们将评估遗传和药物清除衰老细胞和抗炎的效果 感觉学。我们将建立一个管道来确定单个衰老细胞的表观遗传年龄 DNA甲基化图谱，有益与有害衰老细胞的候选预测因子。在整个过程中 我们将与加州大学圣地亚哥分校表观基因组学中心及其生物分析核心密切合作 跟踪数据质量的项目，通过结合批次和其他技术将研究设计与下游分析联系起来 协变量，为验证研究的目标选择提供信息，并为所有人组织元数据和相关数据 实验。最后，我们将基于我们的开源软件创建一个元数据存储库 小组在其他大型项目中组织所有原始和处理的数据，提供综合成果文件， 处理项目使用的管道和分析工具，并确保所有项目数据是公平的、可互操作的 并遵循社区标准格式。使用此存储库，我们将把项目数据传输到联合体 组织和数据协调中心(CODCC)并与财团中的其他小组协作 共享数据和资源。

PROJECT SUMMARY The Data Analysis Core will computationally define and characterize transcriptomic and epigenomic signatures of cellular senescence in murine brain, bone marrow, colon, breast and liver cell types from healthy male and female young and old mice. We will use established, scalable pipelines to process data generated by the Biological Analysis Core and create an integrated map of brain, bone marrow, colon, breast and liver cell types using cellular profiles derived from all single cell sequencing and imaging assays together. Using this integrated map, we will identify populations of senescent cells within each tissue-resident cell type based on gene expression and epigenomic profiles of known cellular senescence markers, and define both heterogeneous sub- types of senescent cells as well as ‘senescent-like’ cells with non-canonical profiles. For each senescent and senescent-like sub-type, we will define its cis-regulatory programs including candidate cis-regulatory elements (cCREs), chromatin states, transcriptional regulators and target genes of cCRE activity (i.e., gene enhancer – promoter networks), as well as their spatial orientation and micro-environment. We will characterize changes in the abundance and cis-regulation of senescent and senescent-like cell sub-types as well as cell types in the senescent niche across life span and linked to sex, cell type and tissue region. This integrated transcriptomic and epigenomic map of senescent cells will define and resolve senescent cells better than transcriptome alone. We will evaluate the effects of genetic and pharmacologic clearance of senescent cells and anti-inflammatory senomorphics. We will establish a pipeline to determine epigenetic age of single senescent cells based on their DNA methylation profile, a candidate predictor of beneficial versus detrimental senescent cells. Throughout the project we will work closely with the UCSD Center for Epigenomics and the Biological Analysis Core of this project to track data quality, link study design to downstream analyses by incorporating batch and other technical covariates, inform selection of targets for validation studies, and organize meta-data and associated data for all experiments. Finally, we will create a meta-data repository based on open-source software employed by our group in other large-scale projects to organize all raw and processed data, provide integrated results files, processing pipelines and analytical tools used by the project, and ensure all project data is FAIR, interoperable and adheres to community standard formats. Using this repository, we will transfer project data to the Consortium Organization and Data Coordination Center (CODCC) and collaborate with other groups in the consortium to share data and resources.