STAMP technology to enable single-cell and isoform-sensitive detection of RBP sites

STAMP 技术可实现 RBP 位点的单细胞和亚型敏感检测

• 批准号: 10277360
• 负责人: Eugene Wei-Ming Yeo
• 金额: $ 99.54万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10277360
• 关键词: Adoption; Amino Acids; Antibodies; Binding; Binding Proteins; Binding Sites; Biological; Birth; Cells; Collection; Communities; Coupled; Data; Data Set; Detection; Disease; Elements; Gene Expression; Genetic Translation; Genomics; Goals; Grant; Human; Immunoprecipitation; Label; Libraries; Life Cycle Stages; Locales; Measurement; Measures; Mediating; Messenger RNA; Metabolism; Methodology; Methods; Modification; Molecular; Monitor; Morphologic artifacts; National Human Genome Research Institute; Nature; Noise; Protein Isoforms; Protein Subunits; Protocols documentation; RNA; RNA Processing; RNA analysis; RNA-Binding Proteins; Reagent; Regulatory Element; Reproducibility; Research; Resolution; Resources; Ribosomal Proteins; Ribosomes; Role; Sampling; Signal Transduction; Site; Specificity; Structure; Surveys; Technology; Testing; Third Generation Sequencing; Time; Transcript; Translations; Untranslated RNA; Work; analytical tool; apoB mRNA editing catalytic subunit; base; cell type; computer framework; crosslink; design; detection limit; flexibility; genomic RNA; improved; insight; nanopore; new technology; novel; paralogous gene; programs; response; ribosome profiling; single cell analysis; single molecule; technological innovation; technology development; transcriptome; transcriptome sequencing

PROJECT SUMMARY RNA-binding proteins (RBPs) interact with RNA molecules from synthesis to decay to control their metabolism, subcellular localization, stability and translation. Methods for transcriptome-wide detection of RBP-RNA interactions provide insights into how RBPs regulate gene expression programs and how RNA processing is disrupted in disease state. Despite their association with disease and although the importance of regulating gene expression is well appreciated, only a small fraction of the over 2,000 RBPs identified thus far have known RNA targets and molecular roles. Commonly, immunoprecipitation-based technologies coupled to high throughput (Illumina) sequencing, such as RNA immunoprecipitation (RIP) and Crosslinking Immunoprecipitation (CLIP), and ribosome profiling are used to identify RBP targets and binding sites across the transcriptome. However, these experimental protocols are labor-intensive, require large amounts of input material, are not adaptable to high-throughput workflows. To overcome these limitations, we develop a novel technology, reagent resource, experimental protocols and a computational framework, that we collectively term STAMP (Surveying Targets By APOBEC-Mediated Profiling), for detecting RBP-RNA targets and translation at the single-cell and single- molecule level. In preliminary data we demonstrate, for the first time in the field, discovery of RBP-RNA sites and translation states at single-cell resolution. We anticipate that STAMP can be used reliably to identify RNA targets, binding sites and even extract motifs from a few cells to a single cell, thus effectively increasing limits of detection over current methods by several orders of magnitude. Combined with simultaneous RNA-seq analyses, STAMP will enable the combined identification of RBP binding sites and global measurement of gene expression, a long- standing goal for the gene expression, genomics and RNA communities. As a corollary, even without single cell analyses, STAMP can accept ultra-low input material which enables rare cell-types to be collected and analyzed for RBP-interactomes. By applying STAMP to ribosomal proteins, we extend this approach for single-cell detection of ribosome association while simultaneously measuring gene expression. Our conceptual and technological innovations will, for the first time, enable translation efficiency and RBP-interactomes to be measured at single-cell level and at scale, opening up new paradigms of biological questions.

项目总结