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全基因组染色体构象捕获数据分析的计算方法。

Computational methods for analyzing genome-wide chromosome conformation capture data.

机构信息

Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy.

Department of Life Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy.

出版信息

Curr Opin Biotechnol. 2018 Dec;54:98-105. doi: 10.1016/j.copbio.2018.01.023. Epub 2018 Mar 15.

Abstract

In all organisms, chromatin is packed to fulfil structural constraints and functional requirements. The hierarchical model of chromatin organization in the 3D nuclear space encompasses different topologies at diverse scale lengths, with chromosomes occupying distinct volumes, further organized in compartments, inside which the chromatin fibers fold into large domains and short-range loops. In the recent years, the combination of chromosome conformation capture (3C) techniques and high-throughput sequencing allowed probing chromatin spatial organization at the whole genome-scale. 3C-based methods produce enormous amounts of genomic data that are analyzed using ad-hoc computational procedures. Here, we review the common pipelines and methods for the analysis of genome-wide chromosome conformation capture data, highlighting recent developments in key steps for the identification of chromatin structures.

摘要

在所有生物体中,染色质的包装是为了满足结构约束和功能需求。在 3D 核空间中,染色质组织的层次模型包含了不同尺度的不同拓扑结构,染色体占据不同的体积,进一步组织在隔室中,在隔室中,染色质纤维折叠成大域和短程环。近年来,染色体构象捕获(3C)技术和高通量测序的结合允许在全基因组范围内探测染色质的空间组织。基于 3C 的方法产生了大量的基因组数据,这些数据使用特定的计算程序进行分析。在这里,我们回顾了用于分析全基因组染色体构象捕获数据的常见流程和方法,重点介绍了在识别染色质结构的关键步骤中的最新进展。

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