Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization
Data-Driven Polymer Model for Mechanistic Exploration of Diploid Genome Organization
复制标题
DOI：
10.1016/j.bpj.2020.09.009
复制
发表时间：
2020-11-03
影响因子：
3.4
通讯作者：
Zhang, Bin
中科院分区：
文献类型：
--
作者：
Qi, Yifeng;Reyes, Alejandro;Zhang, Bin
染色体在细胞核内非随机地定位，以协调它们的转录活性。决定全球基因组组织和单个染色体的核定位的分子机制尚未完全理解。我们引入了一个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，因为能量函数是基于一些生物学动机的假设明确写出的。这两个特征将该模型与现有的方法区分开来，并使其对于重建基因组结构和探索基因组组织的原理都很有用。我们进行了广泛的验证，以表明模拟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的重要性，染色体间的相互作用和染色体定位的着丝粒聚类。我们预计，当与Hi-C实验相结合时，聚合物模型将成为研究细胞分化和肿瘤进展后基因组结构大规模重排的有力工具。
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.