ChIP-based methods for the identification of long-range chromatin interactions.

ChIP-based methods for the identification of long-range chromatin interactions.
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DOI:
10.1002/jcb.22116
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发表时间:
2009-05-01
影响因子:
4
通讯作者:
Ruan, Yijun
Ruan, Yijun
中科院分区:
生物学2区
文献类型:
--
作者:
Fullwood, Melissa J.;Ruan, Yijun

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染色质免疫沉淀(ChIP)是研究蛋白质-DNA相互作用的重要技术。全基因组ChIP方法已经取得了很大的成功,但局限于它们不能揭示重要的长距离染色质相互作用。染色体构象捕获(3C)和相关方法能够检测远程染色质相互作用,但繁琐,具有低信噪比,并且不是全基因组的。尽管将ChIP添加到3C(ChIP-3C)中可以降低噪声并增加染色质相互作用检测的特异性,但有人担心ChIP和3C方案的简单混合会导致高水平的假阳性。在这篇文章中,我们剖析了目前的ChIP和3C为基础的方法,讨论的模型,而不是特异性染色质相互作用,并建议的方法来分离特定的染色质复合物从非特异性染色质片段。我们的结论是,基于超声的染色质片段化,基于ChIP的富集,染色质邻近连接和Paired-End Tag超高通量测序的组合将是全基因组范围内,无偏和从头发现的长距离染色质相互作用的成功实施,这将有助于建立一个新兴的领域,在三维空间中研究人类染色质相互作用和基因组调控网络。
Chromatin Immunoprecipitation (ChIP) is an important technique for studying protein-DNA interactions. Whole genome ChIP methods have enjoyed much success, but are limited in that they cannot uncover important long-range chromatin interactions. Chromosome Conformation Capture (3C) and related methods are capable of detecting remote chromatin interactions, but are tedious, have low signal-to-noise ratios, and are not genome-wide. Although the addition of ChIP to 3C (ChIP-3C) would conceivably reduce noise and increase specificity for chromatin interaction detection, there are concerns that simple mixing of the ChIP and 3C protocols would lead to high levels of false positives. In this essay, we dissect current ChIP-and 3C-based methodologies, discuss the models of specific as opposed to non-specific chromatin interactions, and suggest approaches to separate specific chromatin complexes from non-specific chromatin fragments. We conclude that the combination of sonication-based chromatin fragmentation, ChIP-based enrichment, chromatin proximity ligation and Paired-End Tag ultra-high-throughput sequencing will be a winning implementation for genome-wide, unbiased and de novo discovery of long-range chromatin interactions, which will help to establish an emerging field for studying human chromatin interactomes and genome regulation networks in 3-dimensional spaces.
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