Epigenetic Landscape of Chronic Kidney Disease

描述（由申请人提供）：全基因组关联研究（GWAS）已经非常强大，并成功地确定了遗传多态性（SNP）与糖尿病和慢性肾脏疾病（CKD）发展之间的关联。我们的下一个重大挑战是将这些信息转化为了解糖尿病和CKD发展的机制。主要障碍是大多数CKD相关多态性位于基因组编码区之外。因此，模式生物的经典蛋白质生物化学和基因缺失研究尚不能应用。最近的几项开创性研究为此类实验提供了一个新的框架，并表明细胞类型特异性表观基因组可用于理解和注释基因组的非编码区。由于CKD有数百种已建立的SNP，对每种SNP进行单独的实验可能是一项艰巨的任务，因此迫切需要非编码调控区的全基因组细胞类型特异性作图并定义SNP与转录水平之间的相关性。该提案将使用多种方法的组合来剖析糖尿病和慢性肾脏疾病相关多态性与疾病之间的关联。

DESCRIPTION (provided by applicant): Genome wide association studies (GWAS) have been extremely powerful and successful identifying associations between genetic polymorphisms (SNP) and diabetic and chronic kidney disease (CKD) development. Our next big challenge is to translate this information to understand the mechanism of diabetic and CKD development. The major hurdle is that the majority of CKD associated polymorphisms lie outside the coding region of the genome. Therefore classic protein biochemistry and gene deletion studies of model organisms cannot yet be applied. Several recent pioneering studies have provided a novel framework for such experiments and indicate that the cell type specific epigenome can be used to understand and annotate the non-coding region of the genome. As there are hundreds of established SNPs for CKD, performing individual experiments for each SNP could be a daunting task, therefore there is a critical need for genome wide cell type specific mapping of non-coding regulatory regions and defining the correlation between SNP's and transcript levels. The proposal will use a combination of methods to dissect the association between diabetic and chronic kidney disease associated polymorphisms and disease.