4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C analyses from 4C data

The use of 3C-based methods has revealed the importance of the 3D organization of the chromatin for key aspects of genome biology. However, the different caveats of the variants of 3C techniques have limited their scope and the range of scientific fields that could benefit from these approaches. To address these limitations, we present 4Cin, a method to generate 3D models and derive virtual Hi-C (vHi-C) heat maps of genomic loci based on 4C-seq or any kind of 4C-seq-like data, such as those derived from NG Capture-C. 3D genome organization is determined by integrative consideration of the spatial distances derived from as few as four 4C-seq experiments. The 3D models obtained from 4C-seq data, together with their associated vHi-C maps, allow the inference of all chromosomal contacts within a given genomic region, facilitating the identification of Topological Associating Domains (TAD) boundaries. Thus, 4Cin offers a much cheaper, accessible and versatile alternative to other available techniques while providing a comprehensive 3D topological profiling. By studying TAD modifications in genomic structural variants associated to disease phenotypes and performing cross-species evolutionary comparisons of 3D chromatin structures in a quantitative manner, we demonstrate the broad potential and novel range of applications of our method.

基于3C的实验方法已揭示染色质三维组织对基因组生物学核心环节的重要性。然而，3C技术各类变体存在的不同局限性，限制了其应用范围以及可从这类方法中获益的科研领域范畴。为解决这些局限，我们提出4Cin——一种可基于4C测序（4C-seq）或任意类似4C测序的数据（例如源自下一代捕获C技术（NG Capture-C）的数据）生成基因组位点三维模型，并推导其虚拟Hi-C（vHi-C）热图的方法。该方法仅需整合最少4次4C测序实验得到的空间距离数据，即可确定三维基因组组织。从4C测序数据中获得的三维模型及其配套的vHi-C图谱，可用于推断给定基因组区域内的全部染色体相互作用，助力拓扑关联结构域（Topological Associating Domains，TAD）边界的鉴定。因此，相较于其他现有技术，4Cin提供了一种成本更低、更易获取且通用性更强的替代方案，同时可实现全面的三维拓扑分析。通过研究与疾病表型相关的基因组结构变异中的TAD修饰，并以定量方式开展染色质三维结构的跨物种进化比较，我们验证了本方法广阔的应用潜力与全新的应用场景。