基于Hi-C技术识别基因组结构变异及其在肿瘤研究中的应用  

Identification of genomic structure variation based on Hi-C technology and its application in tumor research

作　　者：刘聪[1,2] 张治华 LIU Cong;ZHANG ZhiHua(CAS Key Laboratory of Genome Sciences and Information,Beijing Institute of Genomics,and China National Center for Bioinformation,Chinese Academy of Sciences,Beijing 100101,China;College of Life Sciences,University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院北京基因研究所国家生物信息中心基因组科学与信息重点实验室,北京100101 [2]中国科学院大学生命科学学院,北京100049

出　　处：《中国科学：生命科学》2020年第5期506-523,共18页Scientia Sinica(Vitae)

基　　金：国家重点研发计划主动健康和老龄化科技应对重点专项(批准号:2018YFC2000400);国家自然科学基金(批准号:31871331,31671342,91940304)资助。

摘　　要：基因组结构变异是多种肿瘤发生的重要驱动因素.虽然目前有基于核型分析、PCR免疫荧光和芯片杂交以及高通量测序等技术可用于基因组结构变异的检测,但由于技术的局限性,现今仍缺乏被广泛认可的基因组结构变异检测方法和相应的分析工具.在肿瘤样本中检测基因组结构变异更是面临严峻的挑战.近20年来,染色体构象捕获技术及其衍生的高通量技术Hi-C等,已经为三维基因组结构的解析提供了大量的组学数据.基因组结构变异通常引起三维基因组空间图谱的异常,通过Hi-C图谱的异常来检测结构变异成为一个新的研究方向.基于Hi-C技术的检测方法有其独特的优势,如可以比较准确地检测位于基因组上重复序列区域的结构变异,但也存在一定的局限性,如不能检测小的结构变异等.本文系统回顾了基因组结构变异的主要研究方法、工具及相应的原理等,并重点讨论了运用Hi-C技术检测结构变异的基本原理、技术优势和局限性,最后介绍了该技术在肿瘤研究中的实际应用.Genomic structure variations are important drivers of the occurrence of a variety of tumors. Although there are technologies based on the karyotype analysis, PCR immunofluorescence and Chip hybridization and high-throughput sequencing can be used in the detection of the structure variations, there is still a lack of widely agreed detection technologies and the corresponding analytical tools due to technical limitations. The detection of structure variations in tumor samples is facing a more severe challenge. In the past two decades, chromosome conformation capture technology and its derived high-throughput technologies, such as Hi-C, have provided a great quantity of omics data for the analysis of three-dimensional genome architecture. Since the variation of genome architecture usually causes the abnormality of three-dimensional map of the genome, using the abnormality of Hi-C map to predict structure variations becomes a new research direction. The prediction methods based on Hi-C technology have their unique advantages. For example, they can accurately predict the structural variations located in the repeat sequence of the genome. However, they also have some limitations, such as the inability to predict small structure variations. This paper systematically reviews the main research methods, tools and corresponding principles of structure variations, and focuses on the basic principles, technical advantages and limitations for using Hi-C technology to predict structure variations. Finally, we introduced the practical applications of this technique in tumor research.

关 键 词：Hi-C 基因组结构变异 三维基因组 

分 类 号：R730.43[医药卫生—肿瘤]