Shin Hanjun, Shi Yi, Dai Chao, Tjong Harianto, Gong Ke, Alber Frank, Zhou Xianghong Jasmine
Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90033, USA.
Key Laboratory of Systems Biomedicine, Ministry of Education, Shanghai Center for Systems Biomedicine, Shanghai Jiaotong University, Shanghai 200240, China.
Nucleic Acids Res. 2016 Apr 20;44(7):e70. doi: 10.1093/nar/gkv1505. Epub 2015 Dec 23.
Genome-wide proximity ligation assays allow the identification of chromatin contacts at unprecedented resolution. Several studies reveal that mammalian chromosomes are composed of topological domains (TDs) in sub-mega base resolution, which appear to be conserved across cell types and to some extent even between organisms. Identifying topological domains is now an important step toward understanding the structure and functions of spatial genome organization. However, current methods for TD identification demand extensive computational resources, require careful tuning and/or encounter inconsistencies in results. In this work, we propose an efficient and deterministic method, TopDom, to identify TDs, along with a set of statistical methods for evaluating their quality. TopDom is much more efficient than existing methods and depends on just one intuitive parameter, a window size, for which we provide easy-to-implement optimization guidelines. TopDom also identifies more and higher quality TDs than the popular directional index algorithm. The TDs identified by TopDom provide strong support for the cross-tissue TD conservation. Finally, our analysis reveals that the locations of housekeeping genes are closely associated with cross-tissue conserved TDs. The software package and source codes of TopDom are available athttp://zhoulab.usc.edu/TopDom/.
全基因组邻近连接分析能够以前所未有的分辨率识别染色质接触。多项研究表明,哺乳动物染色体由亚兆碱基分辨率的拓扑结构域(TDs)组成,这些结构域在不同细胞类型中甚至在一定程度上在不同生物体之间似乎都是保守的。识别拓扑结构域是迈向理解空间基因组组织的结构和功能的重要一步。然而,当前用于识别TDs的方法需要大量计算资源,需要仔细调整,并且/或者在结果上存在不一致性。在这项工作中,我们提出了一种高效且确定性的方法TopDom来识别TDs,以及一套用于评估其质量的统计方法。TopDom比现有方法效率高得多,并且仅依赖于一个直观的参数,即窗口大小,我们为其提供了易于实现的优化指南。TopDom还比流行的方向指数算法识别出更多且质量更高的TDs。由TopDom识别出的TDs为跨组织TD保守性提供了有力支持。最后,我们的分析表明管家基因的位置与跨组织保守的TDs密切相关。TopDom的软件包和源代码可在http://zhoulab.usc.edu/TopDom/获取。