Characterizing muscle regulatory elements with mass spectrometry-based proteomics

利用基于质谱的蛋白质组学表征肌肉调节元件

• 批准号: 8611239
• 负责人: Shao-En Ong
• 金额: $ 32.83万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-23 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8611239
• 关键词: Affect; Affinity; Binding; Binding Proteins; Binding Sites; Biological; Biological Assay; Biology; Cell Line; Cells; Chromatin; Complex; Consensus; DNA; DNA-Protein Interaction; Data; Data Set; Deoxyribonucleases; Development; Disease; Engineering; Enhancers; Epigenetic Process; Exhibits; Functional RNA; Gene Expression; Gene Expression Regulation; Genes; Genetic Polymorphism; Genetic Transcription; Genome; Genomics; Goals; Health; Hela Cells; Human; Human Genome; Interferons; Life; Link; Location; Luciferases; Mammalian Cell; Maps; Mass Spectrum Analysis; Measures; Messenger RNA; Methods; Modeling; Modification; Mus; Muscle; Muscle Fibers; Mutation; Myoblasts; Non-Insulin-Dependent Diabetes Mellitus; Pharmaceutical Preparations; Polydactyly; Post-Translational Protein Processing; Protein Binding; Proteins; Proteome; Proteomics; Recruitment Activity; Regulator Genes; Regulatory Element; Role; SHH gene; Schizophrenia; Single Nucleotide Polymorphism; Site; Techniques; Technology; Time; Trans-Activators; Transcript; Variant; Work; base; biological systems; cancer type; cell type; chromatin immunoprecipitation; cohort; epigenomics; genetic regulatory protein; genome wide association study; genome-wide; in vivo; insight; myogenesis; next generation sequencing; novel; novel strategies; programs; promoter; protein complex; protein expression; public health relevance; research study; tool; transcription factor; vector

Abstract Next-generation sequencing and chromatin immunoprecipitation (ChIP) experiments are generating genome-wide datasets of epigenetic modifications that describe cellular states. The recent ENCODE project has generated hundreds of datasets using genome-wide approaches to map protein-DNA interactions. These dynamic chromatin state maps reveal many thousands of putative cis regulatory modules (CRMs) in the genome, far outnumbering the numbers of genes. These cis regulatory modules are thought to modulate gene expression through the recruitment of specific combinations of trans acting factors, such as transcription factors (TF) and non-coding RNAs. In parallel, genome-wide association studies (GWAS) have mapped thousands of single nucleotide polymorphisms (SNPs) in non-coding regions, suggesting that polymorphisms may be altering gene expression by affecting binding of regulatory trans factors to CRMs. Despite these advanced techniques to localize CRMs in the genome, we currently lack robust high throughput approaches to discover the proteins that interact with these CRMs and characterize their functional roles. To achieve this goal, we propose to: (1) experimentally validate the dynamic recruitment of muscle TFs to novel CRMs and study protein-CRM interactions in regulated genes with proteomics analyses; (3) Develop in- vivo bait approaches to observe protein-DNA interactions in live cells. By focusing on genes significantly up- regulated at the transcript and protein level during muscle differentiation, we will compare proteins bound at novel regulatory loci with neighboring control sequences to identify novel TFs bound at candidate CRMs. In addition to building a powerful toolbox for unbiased proteomic characterization of proteins interacting with specific genomic loci, we will apply our technologies to study candidate CRMs and known muscle regulatory loci surround highly regulated genes in the well characterized C2C12 muscle differentiation model. This work will provide genome biologists with new approaches to identify novel transcription factors and a clearer understanding of the functional significance of CRMs in gene regulation.

摘要 下一代测序和染色质免疫沉淀（ChIP）实验正在产生 描述细胞状态的表观遗传修饰的全基因组数据集。最近的ENCODE项目 已经使用全基因组方法生成了数百个数据集来绘制蛋白质-DNA相互作用。这些 动态染色质状态图揭示了细胞中数千个推定的顺式调节模块（CRM）， 基因组的数量远远超过了基因的数量。这些顺式调控模块被认为是调节基因 通过募集反式作用因子的特定组合（例如转录）来表达 转录因子（TF）和非编码RNA。与此同时，全基因组关联研究（GWAS）已经绘制了 在非编码区的数千个单核苷酸多态性（SNP），表明多态性 可能通过影响调节性反式因子与CRM的结合来改变基因表达。尽管有这些 先进的技术定位CRM在基因组中，我们目前缺乏强大的高通量方法， 发现与这些CRM相互作用的蛋白质，并表征其功能作用。 为了实现这一目标，我们提出：（1）实验验证肌肉TF的动态募集， 利用蛋白质组学技术研究受调控基因中蛋白质与CRM的相互作用; 体内诱饵方法观察活细胞中的蛋白质-DNA相互作用。通过关注基因显著提高- 在肌肉分化过程中在转录和蛋白质水平上受到调控，我们将比较在 具有相邻控制序列的新调控基因座，以鉴定结合在候选CRM上的新TF。 除了建立一个强大的工具箱，用于蛋白质相互作用的无偏见蛋白质组学表征 利用特定的基因组位点，我们将应用我们的技术来研究候选的标准物质和已知的肌肉 在充分表征的C2C12肌肉分化模型中，调节基因座围绕高度调节的基因。 这项工作将为基因组生物学家提供新的方法来识别新的转录因子和一种新的转录因子。 更清楚地了解CRM在基因调控中的功能意义。