Analysis of Somatic Mutations in Longitudinal Whole-genome Sequencing Data

纵向全基因组测序数据中的体细胞突变分析

• 批准号: 10836613
• 负责人: Cody Steely
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF KENTUCKY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10836613
• 关键词: Age; Aging; Algorithmic Software; Algorithms; Blood; Body mass index; Cancer Etiology; Cancer Patient; Cardiovascular Diseases; Cells; Collection; Copy Number Polymorphism; DNA; DNA Repair; Data; Data Set; Detection; Disease; Disease Outcome; Elements; Event; Family; Foundations; Frequencies; Generations; Genetic Polymorphism; Genome; Germ Cells; Germ-Line Mutation; Goals; Hematopoiesis; Human; Human Genome; Individual; Malignant Neoplasms; Measures; Mediating; Modeling; Mutation; Organoids; Phenotype; Play; Postdoctoral Fellow; Process; Research; Role; Sampling; Series; Short Tandem Repeat; Single Nucleotide Polymorphism; Somatic Mutation; Testing; Time; Tissues; Training; Universities; Utah; Variant; Work; career; career development; computational pipelines; design; experience; experimental study; genetic pedigree; genome sequencing; human tissue; improved; member; phenotypic data; programs; time use; variant detection; whole genome

PROJECT SUMMARY While recent efforts have focused on better understanding the germline mutation rate of different types of DNA variants, the dynamics of somatic mutations in the human genome are poorly understood. Somatic mutations are a well-known cause of cancer and may play a causative role in other diseases and aging. Analyses of somatic mutations have generally been limited to single-cell or low-coverage studies. To accurately assess the rate of somatic mutations over time would require a longitudinal, high coverage dataset. For ~450 individuals in the Utah CEPH (Centre d'Etude du Polymorphism Humain) pedigrees, blood was drawn at two timepoints approximately 15 years apart. This proposal describes experiments to determine the rate of somatic mutations throughout the human genome by utilizing high-coverage (720x) whole-genome sequencing data at both of these timepoints in a subset of CEPH individuals. The genomes included in this study will be used to determine the rate of somatic mutations and improve our understanding of differences in this rate between individuals. Building on previous work performed at the University of Utah, we will determine the relationship between the germline and somatic mutation rate. Further, using detailed phenotypic data collected for these individuals, experiments will be performed to determine how this rate is correlated with disease outcomes such as cancer and cardiovascular disease. From this work, a series of filtering algorithms will be produced to allow for comprehensive analysis of somatic mutations occurring between two timepoints in the same individual. This dataset provides me with a unique opportunity to study somatic mutations over time using high-quality data. This proposal builds upon my experience in analyzing mobile element-mediated somatic mutations in longitudinal whole-genome data of cancer patients, and my recent work analyzing germline short tandem repeat mutations in the CEPH pedigrees. The K99 portion of this project will focus on determining the rate of somatic mutations in longitudinal, high-coverage whole-genome sequencing data while creating filtering algorithms to improve our detection capabilities. The additional training I will receive during this period will lay the foundation of an independent research program that will determine the significance of somatic mutations in the human genome and how these relate to disease outcomes.

项目概要 虽然最近的努力集中在更好地了解不同物种的种系突变率 对于 DNA 变异的类型，人类基因组中体细胞突变的动态知之甚少。 体细胞突变是众所周知的癌症病因，并且可能在其他疾病和疾病中发挥致病作用。 老化。体细胞突变的分析通常仅限于单细胞或低覆盖率研究。 为了准确评估体细胞突变率随时间的变化需要纵向、高覆盖度 数据集。对于犹他州 CEPH（人类多态性研究中心）谱系中的约 450 名个体来说， 在相隔约15年的两个时间点抽血。该提案描述了实验 利用高覆盖率 (720x) 确定整个人类基因组的体细胞突变率 CEPH 个体子集在这两个时间点的全基因组测序数据。基因组 这项研究中的内容将用于确定体细胞突变率并改善我们的 了解个体之间该比率的差异。以之前的工作为基础 犹他大学，我们将确定种系和体细胞突变率之间的关系。 此外，利用为这些个体收集的详细表型数据，将进行实验 确定该比率与癌症和心血管疾病等疾病结果的相关性。 通过这项工作，将产生一系列过滤算法，以便对 同一个体的两个时间点之间发生的体细胞突变。该数据集为我提供了 这是使用高质量数据研究体细胞突变的独特机会。 该提议建立在我分析移动元件介导的体细胞突变的经验之上 癌症患者的纵向全基因组数据，以及我最近分析种系短的工作 CEPH 谱系中的串联重复突变。该项目的 K99 部分将重点确定 纵向、高覆盖率全基因组测序数据中的体细胞突变率 过滤算法来提高我们的检测能力。在此期间我将接受的额外培训 期间将为独立研究计划奠定基础，该计划将确定 人类基因组中的体细胞突变以及它们与疾病结果的关系。