Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, Banacha 2c, Warsaw 02-089, Poland; Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 103-8657, Japan.
Laboratory of Functional and Structural Genomics, Centre of New Technologies, University of Warsaw, Banacha 2c, Warsaw 02-089, Poland; Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland.
Methods. 2020 Oct 1;181-182:35-51. doi: 10.1016/j.ymeth.2020.05.025. Epub 2020 Jul 6.
In recent years, high-throughput techniques have revealed considerable structural organization of the human genome with diverse regions of the chromatin interacting with each other in the form of loops. Some of these loops are quite complex and may encompass regions comprised of many interacting chain segments around a central locus. Popular techniques for extracting this information are chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and high-throughput chromosome conformation capture (Hi-C). Here, we introduce a physics-based method to predict the three-dimensional structure of chromatin from population-averaged ChIA-PET data. The approach uses experimentally-validated data from human B-lymphoblastoid cells to generate 2D meta-structures of chromatin using a dynamic programming algorithm that explores the chromatin free energy landscape. By generating both optimal and suboptimal meta-structures we can calculate both the free energy and additionally the relative thermodynamic probability. A 3D structure prediction program with applied restraints then can be used to generate the tertiary structures. The main advantage of this approach for population-averaged experimental data is that it provides a way to distinguish between the principal and the spurious contacts. This study also finds that euchromatin appear to have rather precisely regulated 2D meta-structures compared to heterochromatin. The program source-code is available at https://github.com/plewczynski/looper.
近年来，高通量技术揭示了人类基因组具有相当复杂的结构组织，染色质的不同区域以环的形式相互作用。其中一些环非常复杂，可能包含由中心位置周围的许多相互作用的链段组成的区域。提取这些信息的流行技术是通过末端配对标签测序（ChIA-PET）和高通量染色体构象捕获（Hi-C）进行染色质相互作用分析。在这里，我们介绍了一种基于物理的方法，用于从群体平均 ChIA-PET 数据预测染色质的三维结构。该方法使用来自人类 B 淋巴细胞样细胞的经过实验验证的数据，使用探索染色质自由能景观的动态规划算法生成染色质的 2D 元结构。通过生成最优和次优的元结构，我们可以计算自由能和额外的相对热力学概率。然后，可以使用具有应用约束的 3D 结构预测程序生成三级结构。对于群体平均实验数据，这种方法的主要优点是它提供了一种区分主要和虚假接触的方法。这项研究还发现，常染色质似乎具有比异染色质更精确调节的 2D 元结构。程序源代码可在 https://github.com/plewczynski/looper 获得。
