Advancing Ultra Long-read Sequencing and Chromatin Interaction Analyses for Chromosomal and Extrachromosomal Structural Variation Characterization in Cancer

推进超长读长测序和染色质相互作用分析，用于癌症染色体和染色体外结构变异表征

• 批准号: 9889550
• 负责人: Roel GW Verhaak
• 金额: $ 137.78万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-16 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9889550
• 关键词: Adult; Affect; Biological Assay; Brain; Brain Neoplasms; Breast; Cells; Chromatin; Chromatin Interaction Analysis by Paired-End Tag Sequencing; Chromosome Structures; Chromosomes; Classification; Clustered Regularly Interspaced Short Palindromic Repeats; Communities; Complex; Computing Methodologies; Custom; DNA; DNA Sequence; DNA amplification; DNA analysis; Data; Detection; Development; Effectiveness; Evolution; Fluorescent in Situ Hybridization; Gene Expression; Generations; Genes; Genetic Heterogeneity; Genetic Transcription; Genetic Variation; Genetic study; Genome; Genomic DNA; Genomic Instability; Genomics; Glioblastoma; Goals; Heterogeneity; Knowledge; Length; Libraries; Light; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Maps; Measures; Mediating; Metaphase; Methods; Modeling; Molecular; Molecular Profiling; Molecular Structure; Molecular Weight; Nature; Oncogenes; Oncogenic; Patient-Focused Outcomes; Performance; Phase; Preparation; Protocols documentation; RNA Polymerase II; Reaction; Recurrence; Repetitive Sequence; Research; Resolution; Resources; Role; Sampling; Sensitivity and Specificity; Stains; Standardization; Structure; Technology; Transcriptional Regulation; Tumor Suppressor Proteins; Validation; Variant; Work; anticancer research; base; cancer cell; cancer genome; cancer genomics; cancer therapy; cancer type; computational pipelines; empowered; extrachromosomal DNA; genetic evolution; genome-wide; improved; in silico; malignant breast neoplasm; nanopore; neoplastic cell; novel; prognostic signature; sequencing platform; single molecule; tool; treatment strategy; tumor; tumor growth; tumor progression; tumor xenograft; tumorigenic; variant detection

PROJECT SUMMARY Structural variants (SVs) such as deletions, insertions, inversions, duplications, and translocations in cancer genomes can promote tumor progression by perturbing gene structures and expression. Additionally, extrachromosomal DNA (ecDNA)—an extreme form of SV found in a wide range of cancer types—are a reservoir of oncogene amplification and contribute to the genetic heterogeneity and evolution of tumors. Thus, a complete understanding of the structure and distribution of SVs and ecDNAs in tumors would shed light on their roles in tumor progression. However, the ability to detect and characterize SVs and ecDNAs at the molecular level has been limited by existing short-read sequencing approaches: large and complex SVs thwart efforts to detect them and correctly define their structures; and the multi-copy, heterogenous nature of ecDNAs undermines determination of their primary structures. While ecDNAs can be observed by DAPI-staining of metaphase tumor cells, determining their sequence content has typically relied on fluorescence in situ hybridization (FISH) to probe for candidate oncogenes. To support an unbiased and comprehensive molecular approach to the study of SVs, this project will develop and validate emerging genomic technologies that will enable the detection and characterization of complex SVs and ecDNAs as standard practices in cancer genomics. In Aim 1, the read lengths of the nanopore single-molecule sequencing platform will be further extended by improving genomic DNA quality and optimizing library preparation reactions, with the goal of attaining N50 read lengths of 75-100 Kb. Such long read lengths are expected to span many SVs to more effectively reveal their molecular structures and phasing information. In parallel, the recent SV-detecting computational pipeline, Picky, will be optimized to detect molecular signatures of complex SVs and ecDNAs to allow their accurate and sensitive detection in long read sequencing data to >0.8 precision and recall rates. The active transcription of ecDNAs suggests that they are associated with RNA polymerase II transcription complexes, making them suitable for unsupervised detection by the chromatin interaction assay, ChIA-PET. In Aim 2, this method will be employed to map ecDNAs via their association with RNA polymerase II and reveal transcriptionally relevant interactions between ecDNAs and the chromosomes. Computational methods will be developed to specifically detect ecDNA-amplified sequences in ChIA-PET data and their associated oncogenic genes. Additionally, ecDNAs uncovered by ChIA- PET will be targeted by the CRISPR/dCas9-based targeted capture method to physically isolate ecDNA molecules for long-read sequencing and structural characterization. Aim 3 will build on the developed methods to generate a platform for unbiased and unsupervised characterization of SVs and ecDNAs in glioblastoma neurosphere cultures and in xenograft tumor models of glioblastoma, breast, and lung cancer. Taken together, this project will develop methods and tools that will empower the cancer research community to confidently and comprehensively detect SVs and ecDNAs in cancer genomes.

项目摘要 结构变异（SV），如癌症中的缺失、插入、倒位、重复和易位 基因组可以通过扰乱基因结构和表达来促进肿瘤进展。此外，本发明还 染色体外DNA（ecDNA）--一种在多种癌症类型中发现的SV的极端形式--是一个储存库 癌基因的扩增，并有助于遗传异质性和肿瘤的演变。一个完整的 了解SV和ecDNAs在肿瘤中的结构和分布将有助于阐明它们在肿瘤中的作用。 肿瘤进展。然而，在分子水平上检测和表征SV和ecDNAs的能力， 受到现有短读测序方法的限制：大而复杂的SV阻碍了检测它们的努力 并正确定义它们的结构;并且ecDNAs的多拷贝，异质性破坏了 确定其主要结构。DAPI染色可观察到中期瘤细胞中的ecDNAs 细胞，确定它们的序列内容通常依赖于荧光原位杂交（FISH）来探测 寻找候选致癌基因为了支持SV研究的公正和全面的分子方法， 该项目将开发和验证新兴的基因组技术，使检测和 复杂SV和ecDNA的表征作为癌症基因组学中的标准实践。在目标1中， 纳米孔单分子测序平台的读取长度将通过改进基因组测序来进一步延伸。 DNA质量和优化文库制备反应，目标是获得75-100的N50读长 KB.这样长的读段长度预期跨越许多SV以更有效地揭示它们的分子结构 和定相信息。并行地，最近的SV检测计算流水线Picky将被优化以 检测复杂SV和ecDNAs的分子特征，以允许长期准确和灵敏地检测它们。 读取测序数据以>0.8的精确率和召回率。ecDNAs的活跃转录表明它们 与RNA聚合酶II转录复合物相关，使其适合于无监督的 通过染色质相互作用测定ChIA-PET检测。在目标2中，该方法将用于绘制ecDNAs 通过它们与RNA聚合酶II的结合，揭示了ecDNAs之间转录相关的相互作用， 和染色体。将开发计算方法来特异性地检测ecDNA扩增的 ChIA-PET数据中的序列及其相关致癌基因。此外，由ChIA- PET将通过基于CRISPR/dCas 9的靶向捕获方法靶向，以物理分离ecDNA 用于长读序测序和结构表征的分子。目标3将建立在已开发的方法的基础上 为胶质母细胞瘤中SV和ecDNAs的无偏和无监督表征提供平台 在神经球培养物和胶质母细胞瘤、乳腺癌和肺癌的异种移植肿瘤模型中，综合起来看， 该项目将开发方法和工具，使癌症研究界能够自信地， 全面检测癌症基因组中的SV和ecDNAs。