Mapping of transcription factor binding regions in mammalian cells by ChIP: Comparison of array- and sequencing-based technologies
Mapping of transcription factor binding regions in mammalian cells by ChIP: Comparison of array- and sequencing-based technologies
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DOI：
10.1101/gr.5583007
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发表时间：
2007-06-01
期刊：
影响因子：
7
通讯作者：
Snyder, Michael
中科院分区：
文献类型：
--
作者：
Euskirchen, Ghia M.;Rozowsky, Joel S.;Snyder, Michael
最近在绘制转录因子（TF）结合区域方面的进展在很大程度上归功于染色质免疫沉淀（ChIP）技术。我们比较了使用两种不同的ChIP方案在哺乳动物细胞中绘制TF结合区的策略：ChIP与DNA微阵列分析（ChIP芯片）和ChIP与DNA测序（ChIP PET）。我们首先研究了通过分析人类基因组ENCODE区域中的STAT 1靶点来获得强大的ChIP芯片数据集的核心参数，然后将ChIP芯片与ChIP-PET进行了比较。我们设计了各种平铺阵列之间的评分和比较结果的方法，并检查了参数，如DNA微阵列格式，寡核苷酸长度，杂交条件，和竞争对手Cot-1 DNA的使用。使用高密度寡核苷酸阵列、>= 50个碱基（B）的寡核苷酸、竞争者Cot-1 DNA的存在和在微流体站中进行的杂交实现了最佳性能。当靶标识别作为阵列数量的函数进行评估时，80% - 86%的靶标被三个或更多个阵列识别。ChIP-chip与ChIP-PET的比较显示，最高等级的靶标具有较强的一致性，而低等级的靶标具有较少的重叠。由于每种方法都具有独特的优点和缺点，我们发现ChIP-chip和ChIP-PET在检测排名较低的STAT 1靶标的相对能力方面经常是互补的;每种方法都检测到了另一种方法错过的验证靶标。通过合并ChIP芯片和ChIP测序的结果获得最全面的STAT 1结合区域列表。总体而言，本研究提供了使用基于ChIP的技术对TF靶标进行稳健鉴定、评分和验证的信息。
Recent progress in mapping transcription factor (TF) binding regions can largely be credited to chromatin immunoprecipitation (ChIP) technologies. We compared strategies for mapping TF binding regions in mammalian cells using two different ChIP schemes: ChIP with DNA microarray analysis (ChIP-chip) and ChIP with DNA sequencing (ChIP-PET). We first investigated parameters central to obtaining robust ChIP-chip data sets by analyzing STAT1 targets in the ENCODE regions of the human genome, and then compared ChIP-chip to ChIP-PET. We devised methods for scoring and comparing results among various tiling arrays and examined parameters such as DNA microarray format, oligonucleotide length, hybridization conditions, and the use of competitor Cot-1 DNA. The best performance was achieved with high-density oligonucleotide arrays, oligonucleotides >= 50 bases (b), the presence of competitor Cot-1 DNA and hybridizations conducted in microfluidics stations. When target identification was evaluated as a function of array number, 80% - 86% of targets were identified with three or more arrays. Comparison of ChIP-chip with ChIP-PET revealed strong agreement for the highest ranked targets with less overlap for the low ranked targets. With advantages and disadvantages unique to each approach, we found that ChIP-chip and ChIP-PET are frequently complementary in their relative abilities to detect STAT1 targets for the lower ranked targets; each method detected validated targets that were missed by the other method. The most comprehensive list of STAT1 binding regions is obtained by merging results from ChIP-chip and ChIP-sequencing. Overall, this study provides information for robust identification, scoring, and validation of TF targets using ChIP-based technologies.