Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA.
Simons Center for Computational Physical Chemistry, 24 Waverly Place, Silver Building, New York University, New York, NY 10003, USA.
Nucleic Acids Res. 2024 Jan 25;52(2):583-599. doi: 10.1093/nar/gkad1121.
The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXA and Fbn2 mouse genes ranging in size from 50 to 100 kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.
真核生物基因组的结构和动态与基因调控和转录活性密切相关。许多染色体构象捕获实验，如 Hi-C，已经被开发出来，以检测全基因组的接触频率，并量化不同细胞环境和时间依赖过程中的环/隔室结构。然而，要全面了解这些事件，需要对有代表性的染色质和染色体构型进行明确描述。随着 Hi-C 实验产生的数据呈指数级增长，已经开发出许多从接触频率数据中推导出 3D 结构的方法。然而，大多数重建方法使用低分辨率的聚合物模型来预测整体基因组结构。在这里，我们提出了一种布朗动力学（BD）方法，称为 Hi-BDiSCO，用于使用我们基于离散表面电荷优化（DiSCO）模型的介观分辨率染色质模型，从 Hi-C 和 Micro-C 数据中生成 3D 基因组结构。我们的方法将重建与核小体分辨率的染色质模拟相结合，使用适当的生物物理参数。在描述我们的方案之后，我们展示了对大小在 50 到 100kb 之间的 NXN、HOXC、HOXA 和 Fbn2 小鼠基因的应用。这种核小体分辨率的基因组结构为研究与染色质表观基因组调控和人类疾病控制相关的许多生物医学应用铺平了道路。
