Comparisons of Hi–C data sets between cell types and conditions have revealed differences in topologically associated domains (TADs) and A/B compartmentalization, which are correlated with differences in gene regulation. However, previous comparisons have focused on known forms of 3D organization while potentially neglecting other functionally relevant differences. We aimed to create a method to quantify all locus-specific differences between two Hi–C data sets. We developed MultiMDS to jointly infer and align 3D chromosomal structures from two Hi–C data sets, thereby enabling a new way to comprehensively quantify relocalization of genomic loci between cell types. We demonstrate this approach by comparing Hi–C data across a variety of cell types. We consistently find relocalization of loci with minimal difference in A/B compartment score. For example, we identify compartment-independent relocalizations between GM12878 and K562 cells that involve loci displaying enhancer-associated histone marks in one cell type and polycomb-associated histone marks in the other. MultiMDS is the first tool to identify all loci that relocalize between two Hi–C data sets. Our method can identify 3D localization differences that are correlated with cell-type-specific regulatory activities and which cannot be identified using other methods.

中文翻译：

---

基因组结构的联合推断和比对能够表征跨细胞类型的独立于区室的重组。

细胞类型和条件之间 Hi-C 数据集的比较揭示了拓扑相关域 (TAD) 和 A/B 区室化的差异，这些差异与基因调控的差异相关。然而，之前的比较主要集中在已知的 3D 组织形式上，而可能忽略了其他功能相关的差异。我们的目标是创建一种方法来量化两个 Hi-C 数据集之间所有位点特异性差异。我们开发了 MultiMDS，从两个 Hi-C 数据集中联合推断和比对 3D 染色体结构，从而提供了一种全面量化细胞类型之间基因组位点重新定位的新方法。我们通过比较各种细胞类型的 Hi-C 数据来演示这种方法。我们一致发现基因座的重新定位在 A/B 区室评分中差异极小。例如，我们鉴定了 GM12878 和 K562 细胞之间的区室独立重定位，其中涉及在一种细胞类型中显示增强子相关组蛋白标记的位点，在另一种细胞类型中显示多梳相关组蛋白标记的位点。MultiMDS 是第一个识别两个 Hi-C 数据集之间重新定位的所有基因座的工具。我们的方法可以识别与细胞类型特异性调控活动相关且无法使用其他方法识别的 3D 定位差异。