Extensive multiplexing of protein nucleic-acid interactions to comprehensively study gene expression regulation from chromatin to mRNA degradation

广泛多重分析蛋白质-核酸相互作用，全面研究从染色质到 mRNA 降解的基因表达调控

• 批准号: 10716310
• 负责人: Mitchell Guttman
• 金额: $ 7.76万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10716310
• 关键词: 3-Dimensional; Address; Affinity; Amyotrophic Lateral Sclerosis; Antibodies; Bar Codes; Benchmarking; Binding; Binding Proteins; Biological; Biological Assay; CRISPR/Cas technology; Cell Line; Cell Nucleus; Cells; Chromatin; Communities; Complex; Consumption; DNA; DNA Binding; DNA Sequence; DNA mapping; DNA-Binding Proteins; DNA-Directed RNA Polymerase; DNA-Protein Interaction; Data; Data Set; Dependence; Development; Diffuse; Disease; Disease model; Ensure; Gene Expression; Gene Expression Regulation; Generations; Genes; Genetic Transcription; Genomic DNA; Genomics; Goals; High-Throughput Nucleotide Sequencing; Higher Order Chromatin Structure; Histones; Immunoprecipitation; Individual; International; Link; Maps; Measurement; Measures; Medical; Messenger RNA; Methods; Modeling; Modification; Molecular; Mutation; Neurodegenerative Disorders; Neurons; Nucleic Acids; Organism; Patients; Play; Population; Process; Proteins; Protocols documentation; RNA; RNA Sequences; RNA Splicing; RNA-Binding Proteins; RNA-Protein Interaction; Regulation; Research; Research Personnel; Ribonucleases; Role; Sampling; Sensitivity and Specificity; Specificity; Techniques; Technology; Testing; Time; Transcriptional Regulation; Translations; Work; cell type; chromatin immunoprecipitation; chromatin modification; combinatorial; cost; crosslink; empowerment; epigenomics; experimental study; functional genomics; genetic regulatory protein; genome-wide; genomic RNA; genomic data; histone modification; human disease; innovative technologies; insight; interest; locked nucleic acid; mRNA Transcript Degradation; novel; nucleic acid mapping; programs; protein expression; recruit; tool; transcription factor; transcriptome

Although every cell in the body contains the same DNA sequence, mammalian organisms consist of thousands of cell types defined by distinct gene expression programs. How molecular components, including DNA, RNA and proteins, act to control gene expression is a long-standing question. The model whereby regulatory factors diffuse through the nucleus and engage with their cognate DNA and RNA targets through high affinity interactions cannot explain many of the quantitative features required for gene regulation. The observation that many transcription factors and chromatin regulators organize into higher-order structures within the nucleus may explain the quantitative aspects. Yet, we don’t know (i) the DNA binding and spatial organization of most regulators, (ii) what specific components are present within these compartments, and (iii) what role spatial organization plays in gene regulation. The challenge is that we lack methods to measure combinatorial organization of these molecular components and the ability to disrupt compartmentalization and measure its impact on gene regulation. To address this, we are developing cutting-edge genome-scale methods that allow us to measure multiplexed protein binding and spatial organization of DNA. Specifically, we will create genome-wide maps of hundreds of DNA binding proteins including transcription factors, chromatin regulators, histones (with various modifications) and RNA polymerases. We will then explore the RNA-dependence of regulatory proteins localization by comparing spatial organization in the presence and absence of RNase treatment. Finally, we will then disrupt formation of specific regulatory compartments (using Locked Nucleic Acid and/or CRISPR approaches) to understand possible mechanisms of spatial organization in regulation of specific genes. Our results will provide novel capabilities and a framework for understanding how DNA, RNA, and protein molecules work together in 3D space to efficiently regulate gene expression.

虽然身体中的每个细胞都含有相同的DNA序列，但哺乳动物生物体 由不同的基因表达程序定义的数千种细胞类型。多分子 包括DNA、RNA和蛋白质在内的多种成分控制基因表达是一个长期存在的问题。 问题调节因子通过细胞核扩散并与它们的细胞核相互作用的模型 同源DNA和RNA靶点通过高亲和力相互作用不能解释许多 基因调控所需的定量特征。许多转录因子 和染色质调节器在细胞核内组织成更高级的结构可以解释 数量方面。然而，我们不知道（i）大多数的DNA结合和空间组织 调节剂，（ii）这些隔室中存在哪些特定组分，以及（iii） 空间组织在基因调控中的作用。挑战在于我们缺乏方法来 测量这些分子组分的组合组织和破坏 区室化并测量其对基因调控的影响。为了解决这个问题，我们 开发尖端的基因组规模的方法，使我们能够测量多重蛋白质， DNA的结合和空间组织。具体来说，我们将创建一个全基因组图谱， 数百种DNA结合蛋白，包括转录因子、染色质调节因子、组蛋白 (with各种修饰）和RNA聚合酶。然后我们将探讨RNA依赖性， 调节蛋白定位通过比较空间组织的存在和不存在 RNase处理。最后，我们将破坏特定调节区室的形成， （使用锁核酸和/或CRISPR方法）来了解 调控特定基因的空间组织。我们的研究结果将提供新的能力， 理解DNA、RNA和蛋白质分子如何在3D空间中协同工作的框架 来有效地调节基因表达。