Computational methods for detecting patterns of complex genomic variation

检测复杂基因组变异模式的计算方法

• 批准号: 9027203
• 负责人: Vineet Bafna
• 金额: $ 27.52万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9027203
• 关键词: Address; Algorithms; Architecture; Area; Cell Nucleus; Chromosomes; Clinical; Collaborations; Complex; Computing Methodologies; DNA; Data; Data Analyses; Detection; Development; Disease; Double Minutes; Episome; Etiology; Genes; Genetic; Genetic Recombination; Genome; Genomic Instability; Genomic Segment; Genomics; Goals; Health; Homogeneously Staining Region; Human; Human Genome; Immune; Immune response; Immunoglobulin Variable Region; Individual; Knowledge; Lead; Malignant Neoplasms; Mediating; Medical; Methods; Molecular; Nucleotides; Pattern; Phase; Phenotype; Point Mutation; Reporting; Research; Research Personnel; Role; Sampling; Structure; System; Technology; Variant; Viral; Viral Genome; Virus; Work; base; cancer genome; chromothripsis; computerized tools; deep sequencing; design; genome sequencing; genomic variation; immune activation; insight; interest; new technology; pathogen; public health relevance; reconstruction; single molecule; tool; tumor

 DESCRIPTION (provided by applicant): Genomes evolve and diversify through different mechanisms, including small point mutations, but also larger, structural variations (SV). SVs can be mediated by simple repeats and microhomology based recombination (termed 'progressive SVs' in this proposal). However, progressive SV mechanisms cannot explain all forms of large genomic variation; sometimes, more 'complex mechanisms' are needed; examples include Breakage Fusion Bridge, and Chromothripsis. Moreover, there is little understanding of the genetic mechanisms of genome instability that lead to complex SV formation. It is suspected that random viral genome insertions into the genome can on occasion disrupt key genes, causing genome instability and hyper-variability. To address these problems, the proposal will design and implement computational methods to (a) reconstruct and validate episomal structures of viral genome insertions; (b) determine if genomic sequence sampled from tumor genomes has a signature of complex variation; and, (b) phase and sub-type regions with complex SV including KIR and HLA; As clinical/translational applications of genomics come to the forefront, the impact of complex SVs on the phenotype of an individual become increasingly important. Understanding the computational signatures of BFB and Chromothripsis will help sub-type and characterize cancers. The knowledge of KIR/HLA sub-type will be correlated with immune related phenotypes, and the reconstruction of viral episomes will help clarify the etiology of virus mediated cancers. Thus, the proposed set of computational tools will directly impact the translational/medical aspect of genomics.

 描述(由申请人提供)： 基因组通过不同的ff机制进化和多样化，包括小的点突变，但也包括更大的结构变异(SV)。SVS可以通过简单重复和基于微同源的重组(在本提案中称为进行性SVS)来介导。然而，渐进的SV机制不能解释所有形式的大的基因组变异；有时，需要更多的“复杂机制”；例如，断裂融合桥和染色体萎缩症。此外，对导致复杂SV形成的基因组不稳定的遗传机制还知之甚少。人们怀疑，随机的病毒基因组插入基因组有时会扰乱关键基因，导致基因组不稳定和高度变异性。为了解决这些问题，该提案将设计和实施计算方法，以(A)重建和验证病毒基因组插入的上体结构；(B)确定从肿瘤基因组中采样的基因组序列是否具有复杂变异的特征；以及(B)具有复杂SV的阶段和亚型区域，包括KIR和HLA；随着基因组学的临床/翻译应用的前沿，复杂SV对个体表型的影响变得越来越重要。了解BFB和嗜铬细胞症的计算特征将有助于癌症的亚型和特征。对KIR/HLA亚型的了解将与免疫相关表型相关，而病毒表型的重建将有助于阐明病毒介导的癌症的病因。因此，拟议的一套计算工具将直接影响基因组学的翻译/医学方面。