Center for Theoretical Biological Physics, Rice University, Houston, TX, USA; ICTP South American Institute for Fundamental Research, Instituto de Física Teórica, UNESP - 01140-070, São Paulo, SP, Brazil.
Center for Theoretical Biological Physics, Rice University, Houston, TX, USA; Instituto de Biociências, Letras e Ciências Exatas, UNESP - Univ. Estadual Paulista, Departamento de Física, São José do Rio Preto, SP, Brazil.
J Mol Biol. 2021 Mar 19;433(6):166700. doi: 10.1016/j.jmb.2020.10.034. Epub 2020 Nov 6.
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，人们付出了巨大的努力来获取基因组的三维（3D）结构，以期了解结构如何影响基因调控和表达。染色体构象捕获技术（如 Hi-C）在揭示确定染色质组织所需的定量信息方面发挥了关键作用。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 图谱提供的实验数据相关的三维结构的集合是必要的。这些理论进展不仅超越了结构信息，还开始提供对控制基因组组装和功能的基础机制的理解。然而，最近的理论工作主要集中在单个染色体结构上，忽略了这样一个事实，即在完整的细胞核中，染色体之间的相互作用在其组织中起着核心作用。为了克服这一限制，MiChroM（最小染色质模型）已被修改为能够进行这些多染色体模拟。它已被升级为一个快速且可扩展的软件版本，能够通过 OpenMM Python API 使用 GPU 执行染色体模拟，称为 Open-MiChroM。为了验证这个新版本的效率，对 GM12878 个体常染色体进行了分析，并与早期的研究进行了比较。随后进行了包括人类四个最大染色体（C1-C4）在内的多链模拟。这些模拟展示了这种新方法的全部威力。与 Hi-C 数据的比较表明，这些多个染色体相互作用对于更准确地与实验结果一致是必不可少的。在不改变原始 MiChroM 势的情况下，现在可以预测实验观察到的染色体间接触。Open-MiChroM 的可扩展性允许进行更具挑战性的研究，研究多个链之间的相互作用，并朝着更高分辨率的染色体模型发展。
