Error-suppressed whole genome sequencing for genotoxicant-induced structural variant detection

用于基因毒物诱导的结构变异检测的错误抑制全基因组测序

• 批准号: 10590370
• 负责人: THOMAS EDWARD WILSON
• 金额: $ 41.84万
• 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: 2023-07-14 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10590370
• 关键词: Address; Adopted; Affect; Alkylating Agents; Base Pairing; Basic Science; Biological Assay; Bone Marrow Purging; Bone Marrow Transplantation; Brain; Cell Line; Cells; Chemicals; Chromosome Breakage; Comet Assay; Constitution; Constitutional; Copy Number Polymorphism; DNA; DNA Repair; Data; Detection; Disease; Double Strand Break Repair; Ensure; Environmental Exposure; Epigenetic Process; Equilibrium; Evaluation; Event; Evolution; Exposure to; Frequencies; Gene Fusion; Genes; Genetic Diseases; Genetic Predisposition to Disease; Genome; Genomics; Goals; Hazard Identification; Heterogeneity; High-Throughput Nucleotide Sequencing; Human; Human Genetics; Inherited; Lead; Libraries; Ligation; Malignant Neoplasms; Materials Testing; Methods; Micronucleus Tests; Modeling; Molecular; Morphologic artifacts; Mosaicism; Mus; Mutagenesis; Mutagens; Mutation; Mutation Detection; Nature; Noise; Patients; Performance; Pilot Projects; Process; Protocols documentation; Risk; Risk Factors; Signal Transduction; Single Nucleotide Polymorphism; Specificity; Specimen; Testing; Tissues; Toxic effect; Toxicogenetics; Variant; Work; Yeasts; artemis; clastogen; cost effectiveness; design; disorder risk; follow-up; genome sciences; genome sequencing; genome-wide; genotoxicity; hazard; in vivo; inter-individual variation; interest; mosaic; mutant; population survey; prevent; response; screening; success; targeted nucleases; tool; translational potential; variant detection; whole genome

Project Summary Structural variants (SVs) are an important class of human genetic alteration that creates large changes in genomic content in single mutational events. Copy number variants (CNVs) change the representation of thousands to millions of DNA base pairs, potentially including multiple genes, whereas copy number neutral inversions and translocations lead to gene fusions and dysregulation of epigenetic control mechanisms. SVs and CNVs are critical drivers of cancer, a primary mechanism of constitutional germline genetic disease, and are increasingly appreciated as an ongoing form of somatic mosaicism affecting the function of tissues. SVs are subject to the same classes of risk factors as single-nucleotide variants (SNVs). These factors, which lead to inter-individual variation in lifetime mutation burden and therefore disease risk, include inherited predispositions based on DNA repair capacity and environmental exposures to mutagenic genotoxicants. Genotoxicants that induce disruption or breakage of chromosomes are known as clastogens. Importantly, assays commonly used to identify clastogens or double-strand break (DSB)-inducing genotoxicants are non-specific and fail to reveal whether specific agents lead to new, stable SV junctions in cells and, if so, what the nature and distribution of those junctions is. There is a large need for assays that can efficiently reveal SV mutagens via definitive, positive readouts of breakpoint junctions, the molecular endpoint of interest to toxicologists. Such an assay would be highly impactful in the genome sciences as a way of surveying populations of cells for mosaic SV mutations, including in studies of hazard identification and evaluation, as well as in basic science studies of cancer evolution and heterogeneity, tissue somatic mosaicism, and DSB repair mechanisms. SNVs have further demonstrated the great value of error-minimized, high-throughput sequencing for mutation detection and genotoxicant characterization. Led by Duplex Sequencing, such approaches reveal baseline and induced SNV frequencies with exquisite sensitivity by maximizing signal-to-noise ratios. However, prior work on error-minimized sequencing has been largely limited to SNVs. Our data confirm that the approaches do not address the distinct error mechanisms that lead to false SV detections. Our rationale is that an error-minimized sequencing method designed to address the processes that give rise to SV artifacts will be as impactful for SVs as Duplex Sequencing has been for SNVs. This R21 project will devise, develop, and validate such a method and begin to apply it to important genetic toxicology paradigms, with the following aims: (1) Develop a robust svWGS protocol for error-suppressed, non-targeted SV junction sequencing; and (2) Validate svWGS using well-controlled, high-value case examples with translational potential. Our long-term objective is to apply svWGS in detailed characterizations of emerging candidate human clastogens.

项目概要 结构变异（SV）是一类重要的人类基因改变，它会导致人类基因发生巨大变化。 单个突变事件中的基因组内容。拷贝数变异 (CNV) 改变了 数千至数百万 DNA 碱基对，可能包括多个基因，而拷贝数中性 倒位和易位导致基因融合和表观遗传控制机制的失调。 SV 和 CNV 是癌症的关键驱动因素，是体质种系遗传病的主要机制，并且 作为一种影响组织功能的体细胞嵌合体的持续形式，越来越受到人们的重视。 SV 与单核苷酸变异 (SNV) 面临相同类别的风险因素。这些因素， 这导致终生突变负担的个体间差异，从而导致疾病风险，包括遗传性 基于 DNA 修复能力和环境暴露于致突变基因毒物的易感性。 诱导染色体破坏或断裂的基因毒剂被称为断裂剂。重要的是，化验 通常用于识别断裂剂或双链断裂 (DSB) 诱导基因毒物的方法是非特异性的， 未能揭示特定药物是否会在细胞中产生新的、稳定的 SV 连接，如果是的话，其性质和作用是什么？ 这些路口的分布是。迫切需要能够通过以下方式有效揭示 SV 诱变剂的检测方法： 断点连接的明确、阳性读数，这是毒理学家感兴趣的分子终点。这样一个 作为一种调查细胞群嵌合体的方法，测定法将在基因组科学中产生巨大影响 SV突变，包括危害识别和评估研究以及基础科学研究 癌症进化和异质性、组织体细胞镶嵌和 DSB 修复机制。 SNV 进一步证明了错误最小化、高通量测序的巨大价值 突变检测和遗传毒物表征。以双工测序为主导，此类方法揭示了 通过最大化信噪比，以精致的灵敏度测量基线和感应 SNV 频率。然而， 先前关于错误最小化测序的工作很大程度上局限于 SNV。我们的数据证实 这些方法没有解决导致错误 SV 检测的独特错误机制。我们的理由是 旨在解决产生 SV 伪影的过程的错误最小化测序方法将是 对于 SV 的影响就像双工测序对于 SNV 的影响一样。该 R21 项目将设计、开发和 验证这种方法并开始将其应用于重要的遗传毒理学范式，其目标如下： (1) 开发稳健的 svWGS 方案，用于错误抑制、非靶向 SV 连接测序；和（2） 使用控制良好、具有转化潜力的高价值案例来验证 svWGS。我们的长期 目标是将 svWGS 应用于新兴候选人类断裂剂的详细表征。