Single Cell Chromatin Profiling in Kidney Tissue

肾脏的功能取决于以特定空间排列组织的多种特化细胞类型的协调作用。由于缺乏深入的分子表型分析，在了解疾病发病机制和开发肾脏疾病的生物标志物和治疗方法方面的进展受到阻碍。 肾活检的组织询问技术几十年来没有改变。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响应损伤以及修复和再生期间的细胞类型特异性分子特性。 虽然在肾组织的单细胞转录组学分析方面取得了进展，但应用新的基因组技术来定义表观基因组却落后了。这种知识上的差距是至关重要的，因为大多数与CKD相关的疾病变异都映射到远端调控元件，这些元件通常是细胞类型特异性基因组增强子。确定这些调控区的功能及其对基因表达的影响是有限的，缺乏详细的信息，在正常和患病的人肾组织中的特定肾单位段细胞的染色质状态。 染色质免疫沉淀测序（ChIP-seq）是一种标测表观遗传修饰的标准方法，它需要的起始材料明显多于肾脏活检中可用的起始材料。此外，该方法具有高背景并且缺乏容易用于单细胞染色质谱分析的灵敏度。为了应对这些挑战，本申请提出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。我们将建立一个协议，单细胞染色质分析使用最近描述的方法，切割下的目标和标签化（切割和标签）。我们将开发一个生物信息学管道来分析单细胞组蛋白修饰，定义这些表观基因组特征如何在疾病状态下的特定细胞类型中变化，并将这些发现与单细胞转录组学和ATAC-seq数据相结合。这些技术创新将有可能促进肾脏的新机制研究，发现新的治疗靶点，并确定生物标志物来预测疾病进展。 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，以及小鼠和人类类器官中的疾病模型。将这些工具产生的全基因组表观遗传数据与正在为小鼠和人类肾脏开发的基因表达图谱相结合，对研究界来说将是非常有价值的。由于许多与肾脏疾病相关的遗传变异定位于远端调控元件，因此转录组学和表观基因组学数据的结合将显著扩展这些数据集的能力，以产生关于疾病机制的假设，并对新的靶基因和信号通路进行推断。

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