Core A: Single Cell Profiling and Bioinformatics Core

核心 A：单细胞分析和生物信息学核心

• 批准号: 10332339
• 负责人: Koichi Takahashi
• 金额: $ 42.63万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-08 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10332339
• 关键词: Animals; Bioinformatics; Biological; Biometry; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Chromium; Clinical; Clinical Management; Communities; Complex; Computer Analysis; Computer software; Cross-Sectional Studies; DNA; DNA sequencing; Data; Data Analyses; Data Set; Data Storage and Retrieval; Development; Early Diagnosis; Ecosystem; Elderly; Ensure; Environmental Risk Factor; Epidemiology; Epigenetic Process; Evolution; Exposure to; Gene Frequency; Generations; Genomics; Goals; Growth; Hematologic Neoplasms; Hematopoiesis; Human; Individual; Infection; Lead; Malignant - descriptor; Malignant Neoplasms; Measures; Methodology; Mission; Molecular; Molecular Analysis; Mus; Mutation; Obesity; Patients; Positioning Attribute; Prevention; Prevention approach; Protein Analysis; Quality Control; Reproducibility; Resolution; Rice; Risk; Risk Factors; Smoking; Statistical Models; Stress; Technology; Time; Universities; Work; base; bioinformatics resource; bisulfite sequencing; chemotherapy; clinically relevant; cohort; data quality; data repository; data sharing; design; epidemiologic data; epidemiology study; epigenomics; experience; genetic variant; genomic platform; large scale data; leukemia; mathematical analysis; mathematical model; modifiable lifestyle factors; modifiable risk; molecular scale; multidimensional data; multiple omics; mutant; novel; programs; response; risk prediction; risk prediction model; risk stratification; sequencing platform; single cell analysis; single cell sequencing; single cell technology; single-cell RNA sequencing; stem cell model; stressor; tool; transcriptome sequencing; transcriptomics

Project Summary/Abstract The Single Cell Sequencing and Bioinformatics Core (Core A) is designed to support all Program Projects in their studies of how external, modifiable risk factors influence the progression of clonal hematopoiesis to hematologic malignancy in mice and humans. Two major themes of the Program – understanding how cells with specific mutations respond to modifiable stressors and evaluating the impact of individual mutant clones on others in the ecosystem – both depend on single-cell analysis of cells. The mission of this Core is to provide advanced technical and analytical platforms to track and characterize human and murine mutant cells at single- cell resolution, followed by bioinformatics and mathematical analyses necessary to interpret the data. The Core will (1) provide high-throughput single-cell genomic analysis and other advanced sequencing platforms to all Projects; (2) will provide bioinformatics analysis of multi-dimensional datasets and facilitate data sharing; and (3) will develop mathematical modeling based on large-scale molecular data from mice and humans. To support the first aim, the core is equipped with various single-cell genomics platforms such as Chromium (10X Genomics) and Tapestri (Mission Bio), which enable high-throughput single-cell RNA and DNA sequencing, as well as single-cell multi-omics approaches (CITE-seq and simultaneous DNA/protein analysis). Dr. Koichi Takahashi, Leader of the Core, has been on the forefront of use of such technologies in evaluating the evolution of hematologic malignancies, making him ideally suited to lead to this Program-specific Core. In the second aim, the Core will provide necessary bioinformatic support in analyzing large-scale epigenetic and transcriptomic data in response to modifiable extrinsic risk factors (infection and obesity in Project 1; chemotherapy and smoking in Project 2) to understand the biological effects of stress on clonal hematopoiesis and malignant transformation. In the third aim, the Core will utilize broad epidemiologic data to develop a mathematical model to predict the risk that CH progresses to frank hematologic malignancy in individuals based on their genetic variants, clone size (as measured by variant allele frequency), and specific exposures to modifiable external risk factors (e.g. smoking, obesity, infection, chemotherapies). Dr. Marek Kimmel, Co-Leader of the Core, has an extensive background in mathematical modeling of stem cell dynamics and cancer and is well-positioned to lead this aspect of the Core. This Core will coordinate data storage and quality controls (QC) to ensure the rigor and reproducibility of the data and facilitate public data sharing. Overall, Core A will provide cutting-edge technical and analytical support for all three proposed Projects and support statistical rigor and reproducibility, with support from Core B. By centralizing data analysis and storage, this Core will facilitate the integration of datasets and cross-sectional analyses in order to optimize crosstalk between the large-scale mechanistic animal and human epidemiology studies in this Program. The work of this Core is central to the Program’s overall goal of elucidating the mechanisms of clonal dynamics in response to modifiable external stressors.

项目摘要/摘要 单细胞测序和生物信息学核心（核心A）旨在支持所有程序项目 他们研究外部，可修改的危险因素如何影响克隆造血的发展 小鼠和人类的血液系统恶性肿瘤。该计划的两个主要主题 - 了解单元格如何 具体突变对可修改的应激源反应并评估单个突变克隆对 生态系统中的其他人 - 都取决于细胞的单细胞分析。该核心的任务是提供 先进的技术和分析平台，以跟踪和表征单一人类和鼠突变细胞 细胞分辨率，其次是解释数据所需的生物信息学和数学分析。核心 将（1）向所有人提供高通量单细胞基因组分析和其他高级测序平台 项目； （2）将提供多维数据集的生物信息学分析并促进数据共享； （3） 将根据小鼠和人类的大规模分子数据开发数学建模。支持 首先，核心与各种单细胞基因组学平台（例如铬（10x基因组））等效 和磁带（Mission Bio），它可以使高通量单细胞RNA和DNA测序以及 单细胞多矩方法（cite-seq和同时进行DNA/蛋白质分析）。 koichi takahashi博士， 核心的领导者一直处于使用此类技术的最前沿评估 血液学恶性肿瘤，使他非常适合导致这种特定程序的核心。在第二个目标中 核心将在分析的大规模表观遗传学和转录组数据中提供必要的生物信息学支持 响应可修改的外在危险因素（项目1的感染和肥胖症；化学疗法和吸烟 项目2）了解压力对克隆造血和恶性转化的生物学作用。 在第三个目标中，核心将利用广泛的流行病学数据来开发数学模型来预测 CH基于其遗传变异的个体中坦率的血液系统恶性肿瘤的风险，克隆 大小（通过变异等位基因频率测量），并对可修改的外部风险因素进行特定的暴露（例如 吸烟，肥胖，感染，化学疗法）。核心共同领导者Marek Kimmel博士拥有广泛的 干细胞动力学和癌症的数学建模背景，并具有很好的位置以领导这一方面 核心。该核心将协调数据存储和质量控制（QC），以确保严格和 数据的可重复性并促进公共数据共享。总体而言，核心A将提供最先进的技术 以及对所有三个提议的项目的分析支持，并支持统计严格和可重复性，并得到支持 从核心B进行集中数据分析和存储，该核心将促进数据集和 横截面分析以优化大型机械动物与人之间的串扰 该计划的流行病学研究。该核心的工作对于该计划阐明的总体目标至关重要 克隆动力学的机制响应可修改的外部压力源。