Significant efforts have been recently made to obtain the three-dimensional (3D) structure of the genome with the goal of understanding how structures may affect gene regulation and expression. Chromosome conformational capture techniques such as Hi-C, have been key in uncovering the quantitative information needed to determine chromatin organization. Complementing these experimental tools, co-polymers theoretical methods are necessary to determine the ensemble of three-dimensional structures associated to the experimental data provided by Hi-C maps. Going beyond just structural information, these theoretical advances also start to provide an understanding of the underlying mechanisms governing genome assembly and function. Recent theoretical work, however, has been focused on single chromosome structures, missing the fact that, in the full nucleus, interactions between chromosomes play a central role in their organization. To overcome this limitation, MiChroM (Minimal Chromatin Model) has been modified to become capable of performing these multi-chromosome simulations. It has been upgraded into a fast and scalable software version, which is able to perform chromosome simulations using GPUs via OpenMM Python API, called Open-MiChroM. To validate the efficiency of this new version, analyses for GM12878 individual autosomes were performed and compared to earlier studies. This validation was followed by multi-chain simulations including the four largest human chromosomes (C1-C4). These simulations demonstrated the full power of this new approach. Comparison to Hi-C data shows that these multiple chromosome interactions are essential for a more accurate agreement with experimental results. Without any changes to the original MiChroM potential, it is now possible to predict experimentally observed inter-chromosome contacts. This scalability of Open-MiChroM allow for more audacious investigations, looking at interactions of multiple chains as well as moving towards higher resolution chromosomes models.

最近已经做出了巨大的努力来获得基因组的三维（3D）结构，目的是了解结构如何影响基因的调控和表达。染色体构象捕获技术（例如Hi-C）对于揭示确定染色质组织所需的定量信息至关重要。作为这些实验工具的补充，共聚物理论方法对于确定与Hi-C图提供的实验数据相关的三维结构的集合是必要的。这些理论上的进展不仅限于结构信息，还开始提供对控制基因组装配和功能的潜在机制的理解。但是，最近的理论工作集中在单一染色体结构上，而没有这样一个事实，在整个细胞核中，染色体之间的相互作用在其组织中起着核心作用。为了克服此限制，对MiChroM（最小染色质模型）进行了修改，使其能够执行这些多染色体模拟。它已升级为快速且可扩展的软件版本，可以通过称为Open-MiChroM的OpenMM Python API使用GPU执行染色体模拟。为了验证此新版本的效率，对GM12878单个常染色体进行了分析，并与早期研究进行了比较。验证之后是包含四个最大人类染色体（C1-C4）的多链模拟。这些仿真证明了这种新方法的全部功能。与Hi-C数据的比较表明，这些多染色体相互作用对于与实验结果更准确地吻合至关重要。无需改变原始MiChroM电位，现在就可以预测实验观察到的染色体间接触。Open-MiChroM的这种可扩展性允许进行更多大胆的研究，研究多链的相互作用以及向更高分辨率的染色体模型发展。