Representing structural haplotypes and complex genetic variation in pan-genome graphs

表示泛基因组图中的结构单倍型和复杂的遗传变异

• 批准号: 9906038
• 负责人: Mark Chaisson
• 金额: $ 38.9万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-10 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9906038
• 关键词: Address; Affect; Alleles; Attention; Cells; Chromosomes; Complement; Complex; Computer software; Copy Number Polymorphism; DNA sequencing; Data; Data Set; Development; Disease; Ensure; Felis catus; Future; Genetic; Genetic Variation; Genome; Genotype; Goals; Graph; Haplotypes; Human; Human Characteristics; Human Genetics; Human Genome; Individual; Infrastructure; Large-Scale Sequencing; Length; Maps; Measures; Methodology; Methods; Minisatellite Repeats; Phase; Population; Resolution; Short Tandem Repeat; Single Nucleotide Polymorphism; Single base substitution; Software Framework; Software Tools; Structure; Variant; base; data standards; design; genome sciences; improved; insertion/deletion mutation; interoperability; novel; open source; pan-genome; paralogous gene; reconstruction; reference genome; software development; success; tool; user-friendly; variant detection; working group; Address; Affect; Alleles; Attention; Cells; Chromosomes; Complement; Complex; Computer software; Copy Number Polymorphism; DNA sequencing; Data; Data Set; Development; Disease; Ensure; Felis catus; Future; Genetic; Genetic Variation; Genome; Genotype; Goals; Graph; Haplotypes; Human; Human Characteristics; Human Genetics; Human Genome; Individual; Infrastructure; Large-Scale Sequencing; Length; Maps; Measures; Methodology; Methods; Minisatellite Repeats; Phase; Population; Resolution; Short Tandem Repeat; Single Nucleotide Polymorphism; Single base substitution; Software Framework; Software Tools; Structure; Variant; base; data standards; design; genome sciences; improved; insertion/deletion mutation; interoperability; novel; open source; pan-genome; paralogous gene; reconstruction; reference genome; software development; success; tool; user-friendly; variant detection; working group

Title: Representing structural haplotypes and complex genetic variation in pan-genome graphs. PROJECT SUMMARY A pan-genome graph (PGG) reference must faithfully reflect structural haplotypes that differ in copy number, order, and orientation, which are currently poorly represented in a linear reference sequence. This effort focuses on the most copy variable and complex regions, including segmental duplications (SDs), inversions, short tandem repeats/variable number tandem repeats (copy-number-variable repeats, CNVRs) and combinations thereof that are frequently excluded or collapsed in reference genomes. The overarching goal of this project is to develop the tool infrastructure enabling the construction of whole-chromosome reference haplotypes that include all of these difficult classes of sequence. There are four specific aims. First, we will develop methods to construct PGGs from haplotype-phased de novo assemblies, ensuring the graph reflects both copy number variation and repeat structure, including CNVRs and SD. Second, we will develop software that will expand SD assembly methods to facilitate the curation of SD loci in PGGs. We will use SD assembly to detect variants specific to individual copies of a duplication, called paralog-specific variants (PSVs), and provide software to reconstruct local haplotype paths through the PGG that describe the different copies. Third, we will design novel methods to exploit single-cell template strand DNA sequencing data (Strand-seq) mapped to PGGs in order to thread chromosome-length "structural haplotypes" through the graph. Therefore, our software tool will allow the physical resolution of haplotypes comprising the full spectrum of structural variation, including inversions and inverted duplications. By virtue of the PSVs, the structural haplotypes will also embed sequence-resolved SDs. Fourth, we will develop a scalable open-source software framework to systematically assess how the inclusion of single-nucleotide variants, short indels, and structural variant classes in the PGG affects variant detection with short-read data. This will enable the optimization of the complexity encoded in the PGG for short-read variant detection. It will additionally provide a comprehensive view on polymorphic and fixed k-mers in human populations. We will develop tools to detect allele-specific k-mers and demonstrate how that enables the rapid genotyping of variants in the PGG based on k-mer composition of a short-read dataset. Once the framework for enhanced genome representation is established, we will focus on improving efficiency, scalability, and computational ease to cater to the needs of a broad range of users in genetics and genome science. This proposal will ensure that the most complex regions of the human genome are encoded into the PGG and that underlying genetic variation is ultimately assessed for association with disease. ​

标题：代表泛基因组的结构单倍型和复杂的遗传变异 图。 项目摘要 泛基因组图（PGG）参考必须忠实地反映拷贝数不同的结构单倍型， 目前在线性参考序列中表示的顺序和方向。这项努力 专注于最复制的变量和复杂区域，包括分段重复（SDS），反转， 简短的串联重复/变量号串联重复（copy-number-variable重复序列，cnvrs）和 其组合经常被排除或折叠在参考基因组中。总体目标 该项目是为了开发工具基础设施，以实现全染色体参考的构建 包括所有这些困难类序列的单倍型。有四个具体目标。首先，我们会的 开发从基于单倍型的de从头组件构造PGG的方法，以确保图形反映 拷贝数变化和重复结构，包括CNVR和SD。其次，我们将开发软件 这将扩大SD组装方法，以促进PGG中SD基因座的策划。我们将使用SD组件 检测特定于单个复制副本的变体，称为旁系同源特异性变体（PSV）和 提供软件，通过PGG重建本地单倍型路径，以描述不同的副本。第三， 我们将设计新的方法来利用单细胞模板链DNA测序数据（Strand-Seq）映射 到PGG，以通过图将染色体长度的“结构单倍型”螺纹。因此，我们的 软件工具将允许单倍型的物理分辨率完成结构变化的完整范围， 包括反转和倒复制。凭借PSV，结构单倍型也将嵌入 序列分辨的SD。第四，我们将开发一个可扩展的开源软件框架 评估如何在PGG中纳入单核苷酸变体，短插入和结构变体类别 使用短阅读数据影响变体检测。这将使在 PGG用于短读变体检测。它还将提供有关多态性和 修复了人口中的K-Mers。我们将开发用于检测特定等位基因的K-Mers的工具，并演示如何 这可以基于短读数据集的K-MER组成在PGG中快速基因分型。 一旦建立了增强基因组表示的框架，我们将专注于提高效率， 可伸缩性和计算易于满足遗传学和基因组中广泛用户的需求 科学。该建议将确保将人类基因组的最复杂地区编码为 PGG和潜在的遗传变异最终被评估为与疾病关联。 になったんです。英语：您可以做的第一件事就是找到最好的方法。