Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, 1050 Childs Way, Los Angeles, California 90089, USA.
National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.
Nat Commun. 2016 May 31;7:11549. doi: 10.1038/ncomms11549.
Three-dimensional (3D) genome structures vary from cell to cell even in an isogenic sample. Unlike protein structures, genome structures are highly plastic, posing a significant challenge for structure-function mapping. Here we report an approach to comprehensively identify 3D chromatin clusters that each occurs frequently across a population of genome structures, either deconvoluted from ensemble-averaged Hi-C data or from a collection of single-cell Hi-C data. Applying our method to a population of genome structures (at the macrodomain resolution) of lymphoblastoid cells, we identify an atlas of stable inter-chromosomal chromatin clusters. A large number of these clusters are enriched in binding of specific regulatory factors and are therefore defined as 'Regulatory Communities.' We reveal two major factors, centromere clustering and transcription factor binding, which significantly stabilize such communities. Finally, we show that the regulatory communities differ substantially from cell to cell, indicating that expression variability could be impacted by genome structures.
三维（3D）基因组结构即使在同系样本中也存在细胞间差异。与蛋白质结构不同，基因组结构具有高度的可变性，这对结构-功能映射构成了重大挑战。在这里，我们报告了一种全面识别 3D 染色质簇的方法，这些簇在群体基因组结构中经常出现，无论是从平均 Hi-C 数据的解卷积数据中，还是从单个细胞 Hi-C 数据集中识别出来的。我们将该方法应用于淋巴母细胞系的基因组结构（在宏观区域分辨率下）群体中，以识别稳定的染色体间染色质簇图集。这些簇中有大量的簇富含特定调节因子的结合，因此被定义为“调节社区”。我们揭示了两个主要因素，着丝粒聚类和转录因子结合，它们显著稳定了这些社区。最后，我们表明调节社区在细胞间有很大差异，这表明表达变异性可能受到基因组结构的影响。
