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.

摘要 人类基因组在个体之间和个体内部都有显著的变异。大量研究 探索了人类群体中的遗传变异，并将各种生殖系多态性与人类 性状和疾病易感性。基因组序列在个体内也有差异，发生在受精卵之后 形成并导致从单个细胞到整个组织的频谱中存在的变化。 这种基因组变异的体细胞嵌合现象已经在表型正常的细胞中很好地建立起来。 个体，并已显示也与一些疾病表型，特别是癌症相关。 然而，这些研究大多局限于较高频率的嵌合现象（例如>5-10%的变异体）。 等位基因频率）。 使这些技术挑战更加复杂的是，每个人体组织表现出明显不同的生长速率。 体细胞镶嵌现象例如，目前估计人类大脑中的每个细胞都含有 数百到几千个体细胞单核苷酸变异（SNV），并且一小部分细胞携带 体细胞拷贝数变异（CNVs）、移动的元件插入（MEI）和短串联重复序列扩增 （可疑交易报告）。相比之下，据报道，体细胞突变率在大型和小型 肠和胃及前列腺的下部。这些比率是通过各种 方法，包括SNP微阵列，批量和单细胞全基因组测序和直接扩增， 以及候选事件的排序，每一个都有其自身的优点和局限性。然而，迄今为止， 是对人体内整个频谱上的人体嵌合体的系统研究， 组织中我们的团队在开发用于识别体细胞嵌合体的工具方面具有丰富的集体经验。 人类大脑，包括最近从全基因组和外显子组测序中对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录转座子。 在这里，我们建议改进，优化，并将我们的方法扩展到其他人体组织，作为 SMaHT倡议将提供一个极好的平台， 探索人体组织间的嵌合现象。我们将分两个阶段实现这一目标： UG 3阶段的这个项目，我们将（1）改善分子测定纳米孔靶向散装捕获和单 细胞测序和（2）改进用于检测来自单细胞的体细胞嵌合现象的计算方法， 批量组织数据，而在UH 3阶段，我们将（3）优化，基准，并验证分子测定高- 跨人体组织的吞吐量应用，以及（4）提高效率、运行时间和结构化报告， 体细胞变异总的来说，这些努力将提高我们在以前被忽视的规模上进行检测的能力 类体细胞变异和扩大的大小范围和频谱，他们可能是 确定。