Bonhoure Nicolas, Bounova Gergana, Bernasconi David, Praz Viviane, Lammers Fabienne, Canella Donatella, Willis Ian M, Herr Winship, Hernandez Nouria, Delorenzi Mauro
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland;
Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; Bioinformatics Core Facility, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland;
Genome Res. 2014 Jul;24(7):1157-68. doi: 10.1101/gr.168260.113. Epub 2014 Apr 7.
Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes.
染色质免疫沉淀结合深度测序(ChIP-seq)实验被广泛用于在整个基因组范围内确定任何感兴趣蛋白质的结合位点,这些蛋白质包括例如转录因子、RNA聚合酶或具有或不具有各种修饰的组蛋白。除了能够确定一种细胞类型在一种条件下的结合位点外,该方法原则上还允许在各种细胞类型、组织和条件下建立并比较结合图谱。然而,这种比较要求样本进行标准化处理。广泛使用的包含分位数标准化步骤的标准化方法,当因子结合在一部分位点上发生变化时表现良好,但可能会遗漏全基因组范围内结合位点的均匀增加或减少情况。我们描述了一种加标调整程序(SAP),与在分析阶段进行干预的常用标准化方法不同,它在免疫沉淀之前需要一个实验步骤。将来自一批外源基因组的恒定少量染色质添加到实验染色质中。然后,这种“加标”染色质作为内部对照,可据此调整实验信号。我们表明,该方法提高了重复样本之间的相似性,并揭示了包括全局和基本均匀变化在内的生物学差异。