Molecular and Computational Tools for Identifying Somatic Mosaicism in Human Tissues

识别人体组织中体细胞镶嵌的分子和计算工具

• 批准号: 10661147
• 负责人: Alan P Boyle
• 金额: $ 40.13万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10661147
• 关键词: Address; Bar Codes; Benchmarking; Biological Assay; Brain; Cataloging; Cell Fraction; Cell Nucleus; Cells; Centrifugation; Cloud Computing; Complement; Computer software; Computing Methodologies; Copy Number Polymorphism; DNA Insertion Elements; Data; Development; Disease susceptibility; Event; Exhibits; Frequencies; Gastric Glands; Gene Frequency; Genetic Polymorphism; Genome; Genomics; Goals; Human; Human Genome; Individual; Inherited; Investigation; Large Intestine; Link; Malignant Neoplasms; Molecular; Mosaicism; Mutation Detection; Output; Percoll; Phase; Phenotype; Population; Preparation; Prevalence; Prostate; Reporting; Resolution; Retrotransposon; Running; Short Tandem Repeat; Single Nucleotide Polymorphism; Small Intestines; Somatic Mutation; Standardization; Structure; Surveys; Technology; Testing; Time; Tissues; Variant; Work; analysis pipeline; computerized tools; density; disease phenotype; exome sequencing; experience; genetic variant; genome sequencing; high throughput screening; human tissue; improved; innovation; iodixanol; mosaic; nanopore; open source; personalized approach; single cell sequencing; software repository; targeted sequencing; tool; trait; whole genome; zygote

Abstract Human genomes harbor significant variation both between and within individuals. Numerous studies have explored inherited variation across human populations and linked various germline polymorphisms to human traits and disease susceptibility. Genomic sequences also vary within an individual, occurring after zygote formation and leading to variation present in a frequency spectrum ranging from individual cells to entire tissues. This somatic mosaicism of genome variation has been well established in cells of phenotypically normal individuals and has been shown to also be associated with some disease phenotypes, particularly cancers. However, these investigations have been mostly limited to higher frequency mosaicism (e.g. >5-10% variant allele frequency) due to technical limitations in both molecular assays and computational methodology. Compounding these technological challenges is that each human tissue exhibits apparently different rates of somatic mosaicism. For example, it is currently estimated that each cell within the human brain contains hundreds to a few thousand somatic single-nucleotide variants (SNVs) and that a smaller fraction of cells harbor somatic copy number variations (CNVs), mobile element insertions (MEIs), and short tandem repeat expansions (STRs). In contrast, somatic mutation rates have been reported to be significantly higher in the large and small intestines and lower in gastric and prostatic glands. These rates have been ascertained through a variety of approaches, including SNP microarrays, bulk and single cell whole genome sequencing, and direct amplification and sequencing of candidate events, each with its own advantages and limitations. However, there has yet to be a systematic investigation of human somatic mosaicism across the entire frequency spectrum within human tissues. Our team has extensive collective experience developing tools for identifying somatic mosaicism in the human brain, including recent surveys of SNV prevalence from whole genome and exome sequencing, CNVs from single cell short-read and nanopore genome sequencing, and retrotransposons through targeted capture. Here, we propose to improve, optimize, and extend our approaches to other human tissues as part of the SMaHT initiative, which will provide an excellent platform for systematically identifying, cataloging, and exploring human somatic mosaicism across tissues. We will achieve this through two phases: in the UG3 phase of this project, we will (1) improve molecular assays for nanopore targeted bulk capture and single cell sequencing and (2) improve computational approaches for detecting somatic mosaicism from single cell and bulk tissue data, while in the UH3 phase we will (3) optimize, benchmark, and validate molecular assays for high- throughput application across human tissues and (4) improve efficiency, runtime, and structured reporting of somatic variants. Collectively, these efforts will enhance our ability to detect at scale previously overlooked classes of somatic variation and extend the size range and frequency spectrum for which they may be ascertained.

抽象的 人类基因组在个体之间和内部都具有显着差异。有许多研究 探索了人类种群之间的遗传变异，并将各种种系多态性与人类联系起来 特质和疾病易感性。基因组序列在个体中也有所不同，发生在合子之后 形成并导致频谱中存在变化，从单个细胞到整个组织。 这种基因组变异的体细胞镶嵌物在表型正常的细胞中已经很好地确定 个体，并且已被证明与某些疾病表型有关，尤其是癌症。 但是，这些研究主要限于较高的摩西式（例如> 5-10％的变体 等位基因频率）由于分子测定和计算方法的技术局限性。 加重这些技术挑战的是，每个人体组织都表现出明显不同的速率 躯体镶嵌。例如，目前估计人脑中的每个细胞都包含 数百至数千个体细胞单核苷酸变体（SNV），较小的细胞藏有 体拷贝编号变化（CNV），移动元素插入（MEI）和短串联重复扩展 （strs）。相比之下，据报道，大小的体细胞突变率显着更高 肠道，胃腺和前列腺较低。这些费率已经通过多种 方法，包括SNP微阵列，批量和单细胞全基因组测序以及直接扩增 以及对候选事件的测序，每个事件都有自己的优势和局限性。但是，还没有 成为对人类整个频谱中人类体细胞镶嵌的系统研究 组织。我们的团队具有广泛的集体经验，开发了用于识别体细节镶嵌的工具 人脑，包括最近对整个基因组和外显子组测序的SNV患病率的调查，CNV 从单细胞短读和纳米孔基因组测序，以及通过靶向捕获的逆转座子。 在这里，我们建议在这里改进，优化和扩展我们的方法，作为其他人体组织的一部分 SMAHT倡议将为系统地识别，分类，提供一个出色的平台 并探索跨组织的人类体细胞镶嵌。我们将通过两个阶段实现这一目标： 该项目的UG3阶段，我们将（1）改善纳米孔靶向批量捕获和单个的分子测定 细胞测序和（2）改进计算方法，用于检测单细胞和 批量组织数据，而在UH3阶段，我们将（3）优化，基准和验证分子测定法 跨人类组织的吞吐量应用，（4）提高效率，运行时和结构化报告 躯体变体。总的来说，这些努力将增强我们以前被忽视的大规模检测的能力 躯体变化的类别和扩展尺寸范围和频率频谱可能为此 确定。