Development of an Efficient High Throughput Technique for the Identification of High-Impact Non-Coding Somatic Variants Across Multiple Tissue Types

开发一种高效的高通量技术，用于鉴定跨多种组织类型的高影响力非编码体细胞变异

• 批准号: 10662860
• 负责人: Peter J Park
• 金额: $ 44.83万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10662860
• 关键词: ATAC-seq; Address; Algorithms; Alleles; Benchmarking; Binding; Biology; Brain; Cancer Etiology; Catalogs; Cell division; Chromatin; Chromatin Structure; Computer software; Conceptions; Cost Analysis; DNA; DNA Repair; DNA purification; DNA sequencing; Data; Data Set; Detection; Development; Disease; Genetic Enhancer Element; Genome; Genomic Segment; Genomics; Goals; Human; Human Biology; Individual; Malignant Neoplasms; Methods; Modification; Mosaicism; Mutagens; Mutate; Mutation; Mutation Detection; Normal tissue morphology; Nucleic Acid Regulatory Sequences; Phase; Phenotype; Protocols documentation; Publishing; Recurrence; Research; Sampling; Sensitivity and Specificity; Site; Somatic Mutation; Techniques; Technology; Testing; Tissue Microarray; Tissues; Training; Untranslated RNA; Validation; Variant; age related; base; blastocyst; brain tissue; cell type; computerized tools; cost; cost effective; design; detection method; disorder risk; genetic variant; genome sequencing; human tissue; improved; large datasets; mosaic; promoter; scale up; targeted sequencing; technology development; tool; transcription factor; whole genome; ATAC-seq; Address; Algorithms; Alleles; Benchmarking; Binding; Biology; Brain; Cancer Etiology; Catalogs; Cell division; Chromatin; Chromatin Structure; Computer software; Conceptions; Cost Analysis; DNA; DNA Repair; DNA purification; DNA sequencing; Data; Data Set; Detection; Development; Disease; Genetic Enhancer Element; Genome; Genomic Segment; Genomics; Goals; Human; Human Biology; Individual; Malignant Neoplasms; Methods; Modification; Mosaicism; Mutagens; Mutate; Mutation; Mutation Detection; Normal tissue morphology; Nucleic Acid Regulatory Sequences; Phase; Phenotype; Protocols documentation; Publishing; Recurrence; Research; Sampling; Sensitivity and Specificity; Site; Somatic Mutation; Techniques; Technology; Testing; Tissue Microarray; Tissues; Training; Untranslated RNA; Validation; Variant; age related; base; blastocyst; brain tissue; cell type; computerized tools; cost; cost effective; design; detection method; disorder risk; genetic variant; genome sequencing; human tissue; improved; large datasets; mosaic; promoter; scale up; targeted sequencing; technology development; tool; transcription factor; whole genome

Project summary Somatic mutations accumulate in normal tissues and are increasingly recognized as a crucial determinant of disease risk, especially in age-related conditions and cancer. Somatic mutations show enrichment in portions of the noncoding genome that show “open” chromatin structure, such as active promoter and enhancer elements, because open chromatin is more vulnerable to mutagens. Furthermore, transcription factors binding appears to obstruct DNA repair, increasing the likelihood of forming fixed, double- stranded mutations. The channeling effects of these mechanisms result in a concentration of somatic mutations in restricted, yet critical, regions of the genome. Somatic mutations with an increased likelihood of causing diseases frequently arise at recurrent genomic sites, and often even recurrent mutations at specific bases, allowing for the development of targeted methods with greater sensitivity, lower cost, and higher throughput to identify somatic mutations than traditional sequencing techniques. Present methods for identifying somatic mutations generally utilize deep (≥250X) whole genome sequencing (WGS) and tend to be expensive, create large datasets that are computationally challenging to analyze, and have limited ability to detect somatic variants with very low allele fractions. We propose a two phase approach to developing a new tool to address these shortcomings. In the first phase we will develop a method of detecting somatic mutations using ATAC-seq. ATAC-seq targets the open chromatin regions of the genome so is focused on regions with increased somatic mutations that have an increased likelihood of being biologically meaningful, only incorporates a fraction of the genome creating a more manageable dataset, and allows for deeper sequencing to increase the sensitivity of somatic mutation detection. This phase of the proposal includes three aims: modification of the ATAC-seq protocol to allow for detection of somatic mutations; development of analysis software to analyze the data; and testing of the protocol. In the second phase of the protocol, data obtained from phase one will be used to develop a panel sequencing protocol to further narrow the genomic regions looked at, reduce the cost of the analysis, and allow for extracted DNA to be directly analyzed (rather than the intact chromatin needed for ATAC-seq). This phase will also involve three aims: expansion of ATAC-seq analysis to determine the best regions to include on the sequencing panel; development of the sequencing panel; and testing of the panel on a range of individuals and tissue types. This project will provide rapid and inexpensive methods for the detection of potentially critical somatic mutations in any tissue type. At a research level, it will allow for the analysis of a large number of samples to provide critical information on biologically important somatic mutations and thus be an important tool that will help illuminate the spectrum of somatic mutation in the noncoding genome.

项目摘要 体细胞突变积聚在正常组织中，越来越被认为是至关重要的 疾病风险的决定因素，尤其是在与年龄相关的疾病和癌症中。体细胞突变显示 在表现出“开放”染色质结构的非编码基因组部分的富集，例如活性 启动子和增强子元素，因为开放的染色质更容易受到诱变剂的影响。此外， 转录因子的结合似乎阻碍了DNA修复，增加了形成固定，双重的可能性 滞留的突变。这些机制的通道效应导致​​体细胞浓度 基因组的限制但关键区域的突变。躯体突变的可能性增加 经常在复发基因组部位引起疾病，甚至在特定的 基地，允许开发具有更高灵敏度，较低成本和更高的目标方法 与传统的测序技术相比，要识别体细胞突变的吞吐量。 目前用于识别体细胞突变的方法通常利用深（≥250x）整个基因组 测序（WGS）并且往往很昂贵，创建大型数据集，这些数据集在计算上挑战 分析，并且检测具有非常低等位基因分数的体细胞变体的能力有限。我们提出了两个 开发一种新工具来解决这些缺点的方法。在第一阶段，我们将开发一个 使用ATAC-SEQ检测体突变的方法。 ATAC-SEQ针对的 基因组因此着重于具有增加体细胞突变的区域，而这种突变的可能性增加了 在生物学上有意义，仅包含一小部分基因组创建更易于管理的数据集，并且 允许更深的测序提高体细胞突变检测的灵敏度。这个阶段 提案包括三个目的：修改ATAC-SEQ协议以允许检测体细胞 突变；开发分析软件来分析数据；和协议的测试。 在协议的第二阶段，将使用第一阶段获得的数据来开发面板 测序方案进一步缩小基因组区域的范围，降低分析的成本，并允许 为了直接分析提取的DNA（而不是ATAC-SEQ所需的完整染色质）。这个阶段 还将涉及三个目标：扩展ATAC-SEQ分析，以确定要包括在内的最佳区域 测序面板；测序面板的开发；以及对许多个人的测试 组织类型。 该项目将提供快速且廉价的方法来检测潜在的关键体细胞 任何组织类型的突变。在研究级别上，它将允许大量样本分析 提供有关生物学上重要的体细胞突变的关键信息，因此是一个重要工具 帮助照亮非编码基因组中体细胞突变的频谱。