Mapping heritable chromatin loop variants with allele-specific Hi-C analysis

通过等位基因特异性 Hi-C 分析绘制可遗传的染色质环变体图谱

• 批准号: 10583721
• 负责人: Alan D Attie
• 金额: $ 68.75万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-21 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10583721
• 关键词: 3-Dimensional; ATAC-seq; Address; Affect; Alleles; Architecture; Beta Cell; Binding; Binding Sites; Biological; Biological Models; Biology; Budgets; CRISPR screen; Cell Line; Cell physiology; Cells; Chromatin; Chromatin Loop; Cohort Studies; Collection; Complex; DNA; DNA Sequence; Data; Diabetes Mellitus; Disease; Enhancers; Epigenetic Process; Etiology; Euchromatin; Event; Future; Gene Expression; Genes; Genetic; Genetic Transcription; Genetic Variation; Genetic study; Genome; Genotype; Goals; Heritability; Heterochromatin; Heterozygote; Hi-C; Human; Human Biology; Human Genome; Hybrids; In Situ; Inbred Strains Mice; Insulin Antibodies; Islets of Langerhans; Knowledge; Literature; Mammalian Genetics; Maps; Methods; Modeling; Modernization; Molecular; Mouse Strains; Multiomic Data; Mus; Names; Nature; Non-Insulin-Dependent Diabetes Mellitus; Phenotype; Physiological; Population; Property; Publishing; Quantitative Trait Loci; Regulatory Element; Reporting; Research; Resolution; Role; Sorting; Structure; Structure of beta Cell of islet; Surveys; Technology; Time; Tissues; Transcriptional Regulation; Translating; Untranslated RNA; Variant; Visualization; Work; XCL1 gene; bioinformatics tool; cell type; chromosome conformation capture; cost; data resource; deep learning; deep sequencing; epigenome; epigenomics; functional genomics; genetic variant; genome wide association study; genome-wide; genomic data; human disease; improved; in vivo; insight; invention; islet; male; mammalian genome; mouse genetics; novel; promoter; single-cell RNA sequencing; tool; trait; transcriptome

Project Abstract The organization of 3D architecture of mammalian genome is one of the major mysteries in biology. The invention of genome-wide chromosome conformation capture (3C) technologies, or Hi-C, have revealed a hierarchical 3D genome organization, including compartments corresponding to euchromatin and heterochromatin; with higher sequencing depth, Hi-C data further divided the genome into largely invariant topologically associated domains (TADs), which often serve as the boundary for long-range transcriptional regulation. Recently, with ultra-deep sequencing and improved analysis strategies at kilobase-scale resolution, Hi-C can identify chromatin loops within TADs connecting promoters and cis- regulatory elements in an unbiased fashion. Despite these progresses, an unexplored realm is the relationship between DNA sequence and 3D genome features, especially chromatin loops. It is important to elucidate how the transcription machinery translates the genetic variants into variable events at 3D genome levels and leads to transcriptional or physiological alterations. Here we propose to take an initial step solving the genetics of mammalian 3D genome using a panel of F1-hybrid mouse strains. This is enabled by our new Hi-C pipeline named DeepLoop which can sensitively and robustly identify kb- resolution chromatin loops from low-depth allele-resolved Hi-C data. In aim 1, we will generate comprehensive allele-specific maps of transcriptome, epigenome, and kilobase-resolution 3D genome in β-cells from a panel of 7 F1 mice generated from 8 founder strains, which cover nearly the entire spectrum of mouse genetic diversity. In aim 2, we will carry out integrative analyses to reveal the heritable cis- 3D regulatory modules in β-cells. We will also integrate the existing phenotype QTL, eQTL, and functional genomics data into our analysis. In aim 3, we will create a map of conserved 3D regulome between human and mouse β-cells to infer human biology from mouse genetic data. This project will reveal a large part of the genetics of 3D genome in mouse and serve as a launching pad for future human genome research.

项目摘要 哺乳动物基因组三维结构的组织是生物学中的一大谜团。这个 全基因组染色体构象捕获(3C)技术或Hi-C的发明揭示了 分级3D基因组组织，包括对应于常染色质和常染色质的隔室 异染色质；随着测序深度的增加，Hi-C数据进一步将基因组划分为 不变的拓扑相关结构域(TADS)，通常用作长距离的边界 转录调控。最近，随着超深度测序和改进的分析策略， 千基尺度的分辨率，Hi-C可以识别连接启动子和顺式元件的TADS内的染色质环。 以不偏不倚的方式管理要素。尽管取得了这些进展，但一个尚未探索的领域是 DNA序列与3D基因组特征的关系，特别是染色质环。这很重要 为了阐明转录机制如何将遗传变异翻译成3D中的可变事件 基因组水平并导致转录或生理变化。在这里，我们建议采用首字母 使用一组F1杂交小鼠品系解决哺乳动物3D基因组遗传学的步骤。这是 由我们名为DeepLoop的新Hi-C流水线启用，该流水线可以敏感而稳健地识别kb- 从低深度等位基因分辨的Hi-C数据中分辨染色质环。在目标1中，我们将生成 转录组、表观基因组和千碱基分辨3D基因组的全面等位基因特异性图谱 β-来自8个方正品系的7只F1小鼠的细胞，几乎覆盖了整个谱系 老鼠的遗传多样性。在目标2中，我们将进行综合分析以揭示可遗传的cis-3d β细胞中的调节模块。我们还将整合现有的表型QTL、eQTL和功能 基因组学数据进入我们的分析。在目标3中，我们将创建一个保守的3D调节组地图 人类和小鼠的β细胞从小鼠的遗传数据中推断人类的生物学。这个项目将揭示一个巨大的 小鼠3D基因组遗传学的一部分，并作为未来人类基因组的发射台 研究。