Si-C is a method for inferring super-resolution intact genome structure from single-cell Hi-C data.

Si-C is a method for inferring super-resolution intact genome structure from single-cell Hi-C data.
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DOI:
10.1038/s41467-021-24662-z
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发表时间:
2021-07-16
影响因子:
16.6
通讯作者:
Luo Q
Luo Q
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Meng L;Wang C;Shi Y;Luo Q

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人们迫切需要能够从稀疏和噪声单细胞 Hi-C 数据中有效重建有效的超分辨率完整基因组 3D 结构的方法。在这里,我们在贝叶斯理论框架内开发了单细胞染色体构象计算器(Si-C),并应用这种方法从八个 G1 期单倍体小鼠 ES 细胞的单细胞 Hi-C 数据重建完整的基因组 3D 结构。推断的 100 kb 和 10 kb 结构一致地再现了独立成像实验揭示的染色质组织的已知保守特征。对 10 kb 分辨率 3D 结构的分析揭示了单个细胞中细胞间不同的域结构和域中的超精细结构,例如环。每个划分仓平均 0.2 次接触读取足以让 Si-C 获得可靠的结构。 Si-C 构建的有效超分辨率结构证明了在单个细胞的基因组规模上可视化和研究所有染色质位点之间相互作用的潜力。从单细胞 Hi-C 数据构建有效的超分辨率完整基因组 3D 结构对于研究染色体折叠至关重要。在这里,作者开发了一种方法,可以在基因组规模上可视化和研究单个细胞中的染色体折叠
There is a strong demand for methods that can efficiently reconstruct valid super-resolution intact genome 3D structures from sparse and noise single-cell Hi-C data. Here, we develop Single-Cell Chromosome Conformation Calculator (Si-C) within the Bayesian theory framework and apply this approach to reconstruct intact genome 3D structures from single-cell Hi-C data of eight G1-phase haploid mouse ES cells. The inferred 100-kb and 10-kb structures consistently reproduce the known conserved features of chromatin organization revealed by independent imaging experiments. The analysis of the 10-kb resolution 3D structures reveals cell-to-cell varying domain structures in individual cells and hyperfine structures in domains, such as loops. An average of 0.2 contact reads per divided bin is sufficient for Si-C to obtain reliable structures. The valid super-resolution structures constructed by Si-C demonstrate the potential for visualizing and investigating interactions between all chromatin loci at the genome scale in individual cells. Constructing valid super-resolution intact genome 3D structures from single-cell Hi-C data is essential in investigating chromosome folding. Here the authors develop a method that makes it possible to visualize and investigate chromosome folding in individual cells at the genome scale
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