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定量染色质免疫沉淀(ChIP)分析的计算模型。

A computational model of quantitative chromatin immunoprecipitation (ChIP) analysis.

作者信息

Xie Jingping, Crooke Philip S, McKinney Brett A, Soltman Joel, Brandt Stephen J

机构信息

Department of Medicine, Vanderbilt University, Nashville, Tennessee 37232, USA.

出版信息

Cancer Inform. 2008;6:138-46. doi: 10.4137/cin.s295. Epub 2008 Mar 12.

Abstract

Chromatin immunoprecipitation (ChIP) analysis is widely used to identify the locations in genomes occupied by transcription factors (TFs). The approach involves chemical cross-linking of DNA with associated proteins, fragmentation of chromatin by sonication or enzymatic digestion, immunoprecipitation of the fragments containing the protein of interest, and then PCR or hybridization analysis to characterize and quantify the genomic sequences enriched. We developed a computational model of quantitative ChIP analysis to elucidate the factors contributing to the method's resolution. The most important variables identified by the model were, in order of importance, the spacing of the PCR primers, the mean length of the chromatin fragments, and, unexpectedly, the type of fragment width distribution, with very small DNA fragments and smaller amplicons providing the best resolution of TF binding. One of the major predictions of the model was also validated experimentally.

摘要

染色质免疫沉淀(ChIP)分析被广泛用于识别基因组中转录因子(TFs)占据的位置。该方法包括将DNA与相关蛋白质进行化学交联,通过超声处理或酶切消化使染色质片段化,对含有目标蛋白质的片段进行免疫沉淀,然后进行PCR或杂交分析以表征和定量富集的基因组序列。我们开发了一种定量ChIP分析的计算模型,以阐明影响该方法分辨率的因素。该模型确定的最重要变量按重要性排序依次为PCR引物的间距、染色质片段的平均长度,以及出乎意料的片段宽度分布类型,非常小的DNA片段和较小的扩增子能提供最佳的TF结合分辨率。该模型的一项主要预测也通过实验得到了验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b59/2623287/dce653ea391b/cin-6-0137f1.jpg

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