Novel biological insights by utilizing mitochondrial genome information from HuBMAP resources

利用 HuBMAP 资源中的线粒体基因组信息获得新颖的生物学见解

• 批准号: 10530847
• 负责人: Liming Pei
• 金额: $ 52.8万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10530847
• 关键词: ATAC-seq; Address; Affect; Age; Aging; Area; Biochemistry; Bioinformatics; Biological; Biology; Cardiovascular Diseases; Cell Nucleus; Cell physiology; Cells; Cellular biology; DNA Sequence; DNA analysis; Data; Data Set; Databases; Disease; Gender; Gene Expression; Genetic; Genome; Genomics; Health; Human; Human BioMolecular Atlas Program; Human Biology; Human Genome; Imaging Techniques; Immune; Immune System Diseases; Knowledge; Limes; Link; Maps; Mitochondria; Mitochondrial DNA; Mitochondrial Diseases; Nerve Degeneration; Nuclear; Organ; Physiology; RNA; Race; Research Personnel; Resolution; Resources; Role; Spleen; Technology; Testing; Thymus Gland; Tissues; Variant; Visualization software; cell type; cohort; data portal; data resource; epigenome; gene function; genomic data; human disease; improved; insight; lymph nodes; mitochondrial DNA mutation; mitochondrial genome; multiple omics; neglect; novel; single-cell RNA sequencing; tool; transcriptome

PROJECT SUMMARY Although typical scRNA-seq or scATAC-seq data contain 5-25% of reads that map to the mitochondrial DNA (mtDNA) genome, such mtDNA mapped reads are often filtered out or ignored during downstream analysis. The mitochondria generate over 90% of the cellular energy and are central to health and disease. mtDNA mutations directly cause mitochondrial disease. In addition, random somatic mtDNA mutations accumulate with age and are associated with a broad range of aging-related diseases such as immune disorders, cardiovascular disease and neurodegeneration. However, little is understood about whether accumulation of specific mtDNA variants during aging occurs at the same rate across different cell types, organs, age, gender and race. Such insights would substantially improve our understanding of how mtDNA mutations contribute to various human diseases. Accordingly, significant gaps of knowledge in the single-cell biology field include the lack of robust mtDNA analysis tools and how to utilize the rich mtDNA information often neglected in the ever-increasing datasets to obtain new biological insights. We propose to address these knowledge gaps by: (1) develop robust mtDNA analysis workflows and tools integrated with the HuBMAP Portal; (2) systemically analyze mtDNA from single- cell datasets generated by HuBMAP and other resources; (3) determine whether and how prevalent human mtDNA variants impact mitochondrial and cellular function.

项目摘要 虽然典型的scrna-seq或scatac-seq数据包含映射到线粒体DNA的5-25％ （mtDNA）基因组，这种mtDNA映射的读数通常在下游分析中被过滤或忽略。这 线粒体产生超过90％的细胞能量，是健康和疾病的核心。 mtDNA突变 直接引起线粒体疾病。此外，随机体细胞mtDNA突变随着年龄的增长而积累 与广泛的与衰老有关的疾病（例如免疫疾病，心血管疾病）有关 和神经变性。但是，关于特定mtDNA变体的积累的理解很少 在老化期间，在不同的细胞类型，器官，年龄，性别和种族之间以相同的速度发生。这样的见解 将大大提高我们对MTDNA突变如何促进各种人类疾病的理解。 因此，单细胞生物学领域中的大量知识差距包括缺乏强大的mtDNA 分析工具以及如何利用不断增长的数据集中经常忽略的丰富mtDNA信息 获得新的生物学见解。我们建议通过以下方式解决这些知识差距：（1）发展强大的mtDNA 分析与Hubmap门户集成的工作流和工具； （2）从单个的系统分析mtDNA 由Hubmap和其他资源生成的单元数据集； （3）确定是否以及如何流行 mtDNA变体会影响线粒体和细胞功能。