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GSDB:一个从 Hi-C 数据中重建的 3D 染色体和基因组结构数据库。

GSDB: a database of 3D chromosome and genome structures reconstructed from Hi-C data.

机构信息

Department of Computer Science, University of Colorado, Colorado Springs, CO, 80918, USA.

Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, 65211, USA.

出版信息

BMC Mol Cell Biol. 2020 Aug 5;21(1):60. doi: 10.1186/s12860-020-00304-y.

Abstract

Advances in the study of chromosome conformation capture technologies, such as Hi-C technique - capable of capturing chromosomal interactions in a genome-wide scale - have led to the development of three-dimensional chromosome and genome structure reconstruction methods from Hi-C data. The three dimensional genome structure is important because it plays a role in a variety of important biological activities such as DNA replication, gene regulation, genome interaction, and gene expression. In recent years, numerous Hi-C datasets have been generated, and likewise, a number of genome structure construction algorithms have been developed.In this work, we outline the construction of a novel Genome Structure Database (GSDB) to create a comprehensive repository that contains 3D structures for Hi-C datasets constructed by a variety of 3D structure reconstruction tools. The GSDB contains over 50,000 structures from 12 state-of-the-art Hi-C data structure prediction algorithms for 32 Hi-C datasets.GSDB functions as a centralized collection of genome structures which will enable the exploration of the dynamic architectures of chromosomes and genomes for biomedical research. GSDB is accessible at http://sysbio.rnet.missouri.edu/3dgenome/GSDB.

摘要

染色体构象捕获技术的研究进展,如能够在全基因组范围内捕获染色体相互作用的 Hi-C 技术,已经导致了从 Hi-C 数据中重建三维染色体和基因组结构的方法的发展。三维基因组结构很重要,因为它在多种重要的生物活动中发挥作用,如 DNA 复制、基因调控、基因组相互作用和基因表达。近年来,已经产生了大量的 Hi-C 数据集,并且同样地,也已经开发了许多基因组结构构建算法。在这项工作中,我们概述了一个新的基因组结构数据库(GSDB)的构建,以创建一个包含由各种三维结构重建工具构建的 Hi-C 数据集的三维结构的综合存储库。GSDB 包含了来自 12 种最先进的 Hi-C 数据结构预测算法的 32 个 Hi-C 数据集的超过 50,000 个结构。GSDB 作为基因组结构的集中收集,将能够探索染色体和基因组的动态结构,用于生物医学研究。GSDB 可在 http://sysbio.rnet.missouri.edu/3dgenome/GSDB 上访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5215/7405446/50ce76e59239/12860_2020_304_Fig1_HTML.jpg

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