Chromosomes are positioned nonrandomly inside the nucleus to coordinate with their transcriptional activity. The molecular mechanisms that dictate the global genome organization and the nuclear localization of individual chromosomes are not fully understood. We introduce a polymer model to study the organization of the diploid human genome. It is data-driven because all parameters can be derived from Hi-C data; it is also a mechanistic model because the energy function is explicitly written out based on a few biologically motivated hypotheses. These two features distinguish the model from existing approaches and make it useful both for reconstructing genome structures and for exploring the principles of genome organization. We carried out extensive validations to show that simulated genome structures reproduce a wide variety of experimental measurements, including chromosome radial positions and spatial distances between homologous pairs. Detailed mechanistic investigations support the importance of both specific interchromosomal interactions and centromere clustering for chromosome positioning. We anticipate the polymer model, when combined with Hi-C experiments, to be a powerful tool for investigating large-scale rearrangements in genome structure upon cell differentiation and tumor progression.

中文翻译：

---

用于二倍体基因组组织机制探索的数据驱动聚合物模型

染色体非随机地位于细胞核内以与其转录活性相协调。决定全球基因组组织和单个染色体核定位的分子机制尚不完全清楚。我们引入了聚合物模型来研究二倍体人类基因组的组织。它是数据驱动的，因为所有参数都可以从 Hi-C 数据中导出；它也是一个机械模型，因为能量函数是根据一些生物动机假设明确写出的。这两个特征将模型与现有方法区分开来，使其既可用于重建基因组结构，又可用于探索基因组组织的原理。我们进行了广泛的验证，以表明模拟的基因组结构再现了各种各样的实验测量，包括染色体径向位置和同源对之间的空间距离。详细的机制研究支持特定染色体间相互作用和着丝粒聚类对染色体定位的重要性。我们预计聚合物模型与 Hi-C 实验相结合时，将成为研究细胞分化和肿瘤进展时基因组结构大规模重排的有力工具。