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.

项目摘要 结构变异（SV）是一类重要的人类遗传变异，它会在人类基因组中产生巨大的变化。 单个突变事件中的基因组含量。拷贝数变异（CNVs）改变了 数千到数百万个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。SVs和 CNV是癌症的关键驱动因素，是体质性生殖系遗传疾病的主要机制， 越来越多地被认为是影响组织功能的体细胞镶嵌的一种持续形式。 SV与单核苷酸变异（SNV）具有相同的风险因素。这些因素， 导致个体间终生突变负担的差异，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遗传毒物的易感性。 引起染色体分裂或断裂的遗传毒物被称为染色体断裂剂。重要的是， 通常用于鉴定染色体断裂剂或双链断裂（DSB）诱导的遗传毒物是非特异性的， 未能揭示特定试剂是否导致细胞中新的、稳定的SV连接，如果是这样， 这些节点的分布。大量需要可以通过以下途径有效揭示SV诱变剂的测定： 断点连接的确定性阳性读数，毒理学家感兴趣的分子终点。这样的 作为一种调查细胞群体的嵌合体的方法， SV突变，包括在危害识别和评价研究中，以及在 癌症演变和异质性，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的高通量测序对于基因组测序的巨大价值。 突变检测和遗传毒性表征。在双链体测序的领导下，这种方法揭示了 通过最大化信噪比，以极高的灵敏度测量基线和诱发SNV频率。然而，在这方面， 先前关于误差最小化测序的工作主要限于SNV。我们的数据证实， 这些方法没有解决导致错误SV检测的不同错误机制。我们的理由是， 一种误差最小化的排序方法，旨在解决引起SV伪影的过程， 就像双链测序对SNV的影响一样。这个R21项目将设计，开发， 验证这种方法，并开始将其应用于重要的遗传毒理学范例，目的如下： (1)开发用于误差抑制的非靶向SV接头测序的稳健svWGS方案;以及（2） 使用具有平移潜力的良好控制的高价值案例示例来描述svWGS。我们的长期 目的是将svWGS应用于新出现的候选人染色体断裂素的详细表征。