Single Cell Chromatin Profiling in Kidney Tissue

肾脏组织中的单细胞染色质分析

基本信息

批准号：
10373426
负责人：
MICHAEL I RAUCHMAN
金额：
$ 23.63万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-24 至 2023-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10373426
关键词：
ATAC-seq Acute Acute Renal Failure with Renal Papillary Necrosis Address Affect American Atlases Biological Markers Cells ChIP-seq Chromatin Chronic Kidney Failure Clinical Communities DNA Methylation Data Data Set Development Diabetes Mellitus Dialysis procedure Disease Disease Progression Disease model Distal End stage renal failure Enhancers Epigenetic Process Epithelial Cells Funding Opportunities Gene Expression Genes Genetic Transcription Genomics Human Individual Injury Injury to Kidney Kidney Kidney Diseases Kidney Transplantation Knowledge Lead Life Localized Disease Maps Mediating Metabolic Methods Modification Molecular Morbidity - disease rate Mus Natural regeneration Nephrons Neptune Nucleic Acid Regulatory Sequences Organoids Pathogenesis Population Prevalence Process Property Protocols documentation Rare Diseases Regulator Genes Regulatory Element Renal function Research Risk Sampling Signal Pathway Techniques Technology Tissues Tubular formation Untranslated RNA Urine Variant bioinformatics pipeline bioinformatics tool cell type chromatin immunoprecipitation chromatin modification drug discovery effective therapy epigenome epigenomics functional restoration gene repression genetic variant genome wide association study genome-wide histone modification human disease human model in utero injured kidney allograft kidney biopsy kidney cell molecular phenotype mortality nephrogenesis new therapeutic target novel precision medicine predictive marker programs promoter repaired response response to injury single-cell RNA sequencing technological innovation tool transcriptomics

项目摘要

The function of the kidney depends on the coordinated action of multiple specialized cell types organized in a particular spatial arrangement. Progress in understanding disease pathogenesis and in developing biomarkers and therapies for kidney disease has been hindered by a lack of deep molecular phenotyping. Tissue interrogation techniques of kidney biopsies have not changed in several decades. To advance our understanding of kidney development and disease, there is a need to develop tools to define cell-type specific molecular properties in normal kidney tissue, in response to injury, and during repair and regeneration. While progress has been made in single cell transcriptomic analysis of kidney tissue, applying new genomic technologies to define the epigenome has lagged behind. This gap in knowledge is crucial because most disease variants associated with CKD map to distal regulatory elements, which are often cell-type specific genomic enhancers. Determining the function of these regulatory regions and their effect on gene expression is limited by lack of detailed information on the chromatin state of cells in specific nephron segments in normal and diseased human kidney tissue. Chromatin Immunoprecipitation with sequencing (ChIP-seq), a standard method for mapping epigenetic modifications, requires significantly more starting material than is available in a kidney biopsy. Moreover, the method has high background and lacks sensitivity to be readily used for chromatin profiling of single cells. To address these challenges, this application proposes to develop novel cutting edge technological and bioinformatic tools that have not yet been deployed in the kidney, which is the major objective of this R21 funding opportunity. We will establish a protocol for single cell chromatin profiling using a recently described approach, Cleavage Under Targets and Tagmentation (CUT & Tag). We will develop a bioinformatic pipeline to analyze single cell histone modifications, define how these epigenomic features change in specific cell types in disease states, and integrate these findings with single cell transcriptomic and ATAC-seq data. These technological innovations will have the potential to catalyze new mechanistic studies in the kidney, lead to discovery of novel therapeutic targets and identify biomarkers to predict disease progression. The technical and bioinformatic tools we develop will be broadly applicable to investigate kidney diseases in human samples, as well as disease models in mice and human organoids. Integration of genome-wide epigenetic data generated with these tools with gene expression atlases being developed for mouse and human kidneys will be extremely valuable to the research community. Because many genetic variants associated with kidney disease are localized to distal regulatory elements, the combination of transcriptomic and epigenomic data will significantly expand the power of these data sets to generate hypotheses about disease mechanisms, and make inferences about novel target genes and signaling pathways

肾脏的功能取决于在特定空间排列中组织的多种专业细胞类型的协调作用。缺乏深层分子表型，阻碍了理解疾病发病机理以及开发肾脏疾病的生物标志物和疗法的进展。几十年来，肾脏活检的组织询问技术没有改变。为了促进我们对肾脏发育和疾病的理解，需要开发工具来定义正常肾脏组织中的细胞型特异性分子特性，以应对损伤以及修复和再生期间。尽管在肾脏组织的单细胞转录组分析中已经取得了进展，但应用新的基因组技术来定义表观基因组已落后。知识的这种差距至关重要，因为大多数与CKD图与远端调节元素相关的疾病变体通常是细胞类型的特定基因组增强子。确定这些调节区域的功能及其对基因表达的影响受到正常和患病人类肾脏组织中特定肾单位段中细胞染色质状态的详细信息的限制。染色质免疫沉淀与测序（CHIP-SEQ）是一种绘制表观遗传修饰的标准方法，其起始材料比肾脏活检中的起始材料要多得多。此外，该方法具有较高的背景，并且缺乏敏感性，因此很容易用于单细胞的染色质分析。为了应对这些挑战，该应用程序建议开发尚未在肾脏中部署的新型尖端技术和生物信息学工具，这是R21资助机会的主要目标。我们将使用最近描述的方法，目标下的裂解和标记（剪切和标签）建立单细胞染色质分析方案。我们将开发出生物信息学的管道来分析单细胞组蛋白的修饰，定义这些表观基因组特征如何在疾病状态的特定细胞类型中变化，并将这些发现与单细胞转录组和ATAC-SEQ数据相结合。这些技术创新将有可能催化肾脏中的新机械研究，导致发现新型治疗靶标，并识别生物标志物以预测疾病进展。我们开发的技术和生物信息学工具将广泛适用于研究人类样本中的肾脏疾病，以及小鼠和人类器官中的疾病模型。用这些工具生成的全基因组表观遗传数据与为小鼠和人肾脏开发的基因表达图谱的整合对于研究界将非常有价值。由于许多与肾脏疾病相关的遗传变异存在于远端调节元件上，因此转录组和表观基因组数据的组合将显着扩大这些数据集的能力，以产生有关疾病机制的假设，并对新型靶标基因和信号基因的推论进行推断。