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

项目摘要 哺乳动物基因组三维结构的组织是生物学中的主要谜团之一。的 全基因组染色体构象捕获（3C）技术（Hi-C）的发明揭示了 - 分层3D基因组组织，包括对应于常染色质的区室， 随着测序深度的提高，Hi-C数据进一步将基因组分为很大一部分， 不变拓扑关联域（TADs），它通常作为长范围的边界， 转录调控最近，随着超深度测序和改进的分析策略， Hi-C可以识别TADs内连接启动子和顺式- 以无偏见的方式进行监管。尽管有这些进展，一个未探索的领域是 DNA序列和3D基因组特征之间的关系，特别是染色质环。重要的是 为了阐明转录机制如何将遗传变异转化为3D可变事件， 基因组水平，并导致转录或生理改变。在这里，我们建议采取一个初始的 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 通过我们名为DeepLoop的新Hi-C流水线，它可以灵敏而稳健地识别kb， 从低深度等位基因分辨的Hi-C数据分辨染色质环。在aim 1中，我们将生成 转录组、表观基因组和内切酶分辨率3D基因组的全面等位基因特异性图谱， 来自一组7只F1小鼠的β细胞，由8个创始品系产生，几乎涵盖了整个谱系 小鼠遗传多样性的研究在目标2中，我们将进行整合分析，以揭示可遗传的顺式-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QTL， 基因组数据进行分析在目标3中，我们将创建一个保守的3D规则组图， 人类和小鼠β细胞，以从小鼠遗传数据推断人类生物学。该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 research.

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.