Terranova Christopher, Tang Ming, Orouji Elias, Maitituoheti Mayinuer, Raman Ayush, Amin Samirkumar, Liu Zhiyi, Rai Kunal
Department of Genomic Medicine, University of Texas MD Anderson Cancer Center.
The Jackson Laboratory for Genomic Medicine.
J Vis Exp. 2018 Apr 5(134):56972. doi: 10.3791/56972.
Histone modifications constitute a major component of the epigenome and play important regulatory roles in determining the transcriptional status of associated loci. In addition, the presence of specific modifications has been used to determine the position and identity non-coding functional elements such as enhancers. In recent years, chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq) has become a powerful tool in determining the genome-wide profiles of individual histone modifications. However, it has become increasingly clear that the combinatorial patterns of chromatin modifications, referred to as Chromatin States, determine the identity and nature of the associated genomic locus. Therefore, workflows consisting of robust high-throughput (HT) methodologies for profiling a number of histone modification marks, as well as computational analyses pipelines capable of handling myriads of ChIP-Seq profiling datasets, are needed for comprehensive determination of epigenomic states in large number of samples. The HT-ChIP-Seq workflow presented here consists of two modules: 1) an experimental protocol for profiling several histone modifications from small amounts of tumor samples and cell lines in a 96-well format; and 2) a computational data analysis pipeline that combines existing tools to compute both individual mark occupancy and combinatorial chromatin state patterns. Together, these two modules facilitate easy processing of hundreds of ChIP-Seq samples in a fast and efficient manner. The workflow presented here is used to derive chromatin state patterns from 6 histone mark profiles in melanoma tumors and cell lines. Overall, we present a comprehensive ChIP-seq workflow that can be applied to dozens of human tumor samples and cancer cell lines to determine epigenomic aberrations in various malignancies.
组蛋白修饰是表观基因组的主要组成部分,在决定相关基因座的转录状态方面发挥着重要的调控作用。此外,特定修饰的存在已被用于确定增强子等非编码功能元件的位置和身份。近年来,染色质免疫沉淀结合下一代测序(ChIP-seq)已成为确定单个组蛋白修饰全基因组图谱的有力工具。然而,越来越清楚的是,染色质修饰的组合模式,即染色质状态,决定了相关基因组位点的身份和性质。因此,需要由强大的高通量(HT)方法组成的工作流程来分析多种组蛋白修饰标记,以及能够处理大量ChIP-Seq分析数据集的计算分析管道,以便全面确定大量样本中的表观基因组状态。这里介绍的HT-ChIP-Seq工作流程由两个模块组成:1)一个实验方案,用于以96孔板形式从小量肿瘤样本和细胞系中分析多种组蛋白修饰;2)一个计算数据分析管道,它结合现有工具来计算单个标记的占有率和组合染色质状态模式。这两个模块共同促进了以快速有效的方式轻松处理数百个ChIP-Seq样本。这里介绍的工作流程用于从黑色素瘤肿瘤和细胞系的6种组蛋白标记图谱中推导染色质状态模式。总体而言,我们提出了一个全面的ChIP-seq工作流程,可应用于数十个人类肿瘤样本和癌细胞系,以确定各种恶性肿瘤中的表观基因组异常。