Sequence-resolved structural variation of human genomes

人类基因组的序列解析结构变异

• 批准号: 10202688
• 负责人: Evan Eichler
• 金额: $ 63万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-06 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10202688
• 关键词: Algorithms; Alleles; Base Pairing; Complex; Copy Number Polymorphism; DNA; Data; Data Set; Disease; Future; Generations; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genotype; Goals; Graph; Haplotypes; Heritability; Human; Human Genetics; Human Genome; Link; Methods; Mutation; Nucleotides; Phase; Polyploidy; Population; Population Genetics; Property; Research; Resolution; Sampling; Shotguns; Structure; Technology; Time; Variant; Work; base; genetic variant; genome sequencing; genome-wide; human disease; improved; insertion/deletion mutation; insight; novel; paralogous gene; population based; reference genome; single molecule; single molecule real time sequencing; whole genome

Understanding the genetic basis of human disease requires a comprehensive assessment of the full spectrum of human genetic variation. Genome structural variation, including larger deletions, insertions, and inversions (>50 bp), has been more difficult to characterize due to the association with repetitive DNA. The majority of structural variation, including common structural variants or SVs, has not yet been discovered using short-read whole-genome datasets and standard SV callers. Advances in sequencing technology over the last three years, however, have made the systematic discovery of this variation possible for the first time. This proposal focuses on the discovery, sequence resolution, and genotyping of the most complex and under-ascertained forms of human genetic variation, including multi-copy number variants (mCNVs), inversions, and intermediate- size insertions and deletions. We target a diversity panel of 34 human genomes and partition long-read single- molecule, real-time sequencing data using 10X linked reads and Strand-seq data in order to fully phase and sequence-resolve SVs on each human haplotype. Using these long-read sequence data, we further develop a computational graph-based approach to distinguish and assemble distinct copies underlying large mCNVs mapping to high-identity segmental duplications. Finally, we take advantage of the sequence structure, including breakpoints and sequence differences among the copies, to more accurately genotype these variants in a diversity panel of >2,800 human genomes where short-read whole-genome sequence data are already available. The work will develop new methods to characterize more complex forms of human genetic variation and provide fundamental insight into their diversity, mechanism of origin, and mutational properties. This research has the additional benefit that it will improve genome assembly, characterize new human genome sequence, identify a large class of missing genetic variation, and provide us with the ability to systematically explore this form of human genetic variation as part of disease-association studies.

了解人类疾病的遗传基础需要对全谱进行全面评估 人类遗传变异。基因组结构变异，包括较大的缺失、插入和倒位 (>50 bp)，由于与重复 DNA 相关，因此更难以表征。大多数 尚未使用短读长发现结构变异，包括常见的结构变异或 SV 全基因组数据集和标准 SV 调用者。过去三年测序技术的进展 然而，多年来首次系统地发现了这种变异。这个提议 专注于最复杂和尚未确定的基因的发现、序列解析和基因分型 人类遗传变异的形式，包括多拷贝数变异（mCNV）、倒位和中间变异 插入和删除的大小。我们以 34 个人类基因组的多样性为目标，并对长读长的单片段进行分区 分子、实时测序数据，使用 10X 链接读取和 Strand-seq 数据，以便完全定相和 每个人类单倍型上的序列解析 SV。利用这些长读序列数据，我们进一步开发了 基于计算图的方法来区分和组装大型 mCNV 下的不同副本 映射到高同一性片段重复。最后，我们利用序列结构， 包括副本之间的断点和序列差异，以更准确地对这些变异进行基因分型 在超过 2,800 个人类基因组的多样性面板中，短读全基因组序列数据已经 可用的。这项工作将开发新方法来表征更复杂形式的人类遗传变异 并提供对其多样性、起源机制和突变特性的基本见解。这 研究还有额外的好处，它将改善基因组组装，表征新的人类基因组 序列，识别一大类缺失的遗传变异，并使我们能够系统地 作为疾病关联研究的一部分，探索这种形式的人类遗传变异。