Mora Antonio, Huang Xiaowei, Jauhari Shaurya, Jiang Qin, Li Xuri
Joint School of Life Sciences, Guangzhou Medical University and Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences), Guangzhou 511436, PR China.
Affiliated Eye Hospital of Nanjing Medical University, Nanjing 210000, PR China.
Comput Struct Biotechnol J. 2022 Jul 5;20:3796-3813. doi: 10.1016/j.csbj.2022.07.002. eCollection 2022.
This review discusses our current understanding of chromatin biology and bioinformatics under the unifying concept of "chromatin hubs." The first part reviews the biology of chromatin hubs, including chromatin-chromatin interaction hubs, chromatin hubs at the nuclear periphery, hubs around macromolecules such as RNA polymerase or lncRNAs, and hubs around nuclear bodies such as the nucleolus or nuclear speckles. The second part reviews existing computational methods, including enhancer-promoter interaction prediction, network analysis, chromatin domain callers, transcription factory predictors, and multi-way interaction analysis. We introduce an integrated model that makes sense of the existing evidence. Understanding chromatin hubs may allow us (i) to explain long-unsolved biological questions such as interaction specificity and redundancy of mechanisms, (ii) to develop more realistic kinetic and functional predictions, and (iii) to explain the etiology of genomic disease.
本综述在“染色质枢纽”这一统一概念下,探讨了我们目前对染色质生物学和生物信息学的理解。第一部分回顾了染色质枢纽的生物学,包括染色质-染色质相互作用枢纽、核周边的染色质枢纽、围绕RNA聚合酶或长链非编码RNA等大分子的枢纽,以及围绕核仁或核斑点等核体的枢纽。第二部分回顾了现有的计算方法,包括增强子-启动子相互作用预测、网络分析、染色质结构域识别工具、转录工厂预测器和多向相互作用分析。我们引入了一个整合模型,该模型能够解释现有证据。理解染色质枢纽可能使我们(i)解释长期未解决的生物学问题,如相互作用特异性和机制冗余性,(ii)做出更现实的动力学和功能预测,以及(iii)解释基因组疾病的病因。