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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

肾脏的功能依赖于多种特化细胞类型在特定空间安排下的协调作用。由于缺乏深层分子表型，对疾病发病机制的理解以及开发肾脏疾病的生物标志物和治疗方法的进展受到阻碍。