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Cardiac genetic effects across HLBS phenotypes

HLBS 表型的心脏遗传效应

基本信息

批准号：
9521873
负责人：
ARAVINDA CHAKRAVARTI
金额：
$ 43.81万
依托单位：
NEW YORK UNIVERSITY SCHOOL OF MEDICINE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-05-01 至 2020-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9521873
关键词：
ATAC-seq Affect Algorithms Base Pairing Binding Blood Cardiac Cardiovascular Diseases Chromatin Code Collaborations Complex Computing Methodologies DNA DNase I hypersensitive sites sequencing Data Disease Enhancers Family Gene Expression Gene Frequency Gene Targeting Genes Genetic Genetic Transcription Genetic Variation Genome Genomics Genotype Genotype-Tissue Expression Project Heart Heart Diseases Hematological Disease Individual Lead Link Lung Lung diseases Machine Learning Maps Minor Modeling Molecular Peripheral Phenotype Physiology Public Health Publishing Quality Control Regulator Genes Regulatory Element Research Personnel Resources Role Sample Size Sleep Sleep Disorders Testing Tissues Trans-Omics for Precision Medicine United States National Institutes of Health Untranslated RNA Variant Weight base epigenomics functional genomics gene discovery genetic variant genome wide association study genome-wide genome-wide analysis genomic data genomic variation histone modification improved novel novel strategies programs rare variant reverse genetics success trait transcription factor transcriptome sequencing whole genome

项目摘要

Forward genetic genome-wide association studies (GWAS) have successfully mapped thousands of loci regulating disorders of the heart, lung, blood and sleep (HLBS), implicating widespread sequence variation within the non-coding genome. However, their functions, mechanisms of action and how they impact disease is still unclear. To solve this new and important GWAS bottleneck, we use a functional genomics-inspired reverse genetics strategy to identify the `transcriptional machinery' (transcription factors (TF), cis-regulatory elements (CRE), target genes) controlling HLBS-relevant tissue functions and how DNA variants in them affect HLBS diseases. Taking advantage of our long-standing expertise and successes in complex, cardiovascular disorders, and novel computational methods we have recently developed, we propose novel genomics analyses of the Trans-Omics for Precision Medicine (TOPMed) Program phenotypes and their whole genome sequences, together with publicly available epigenomics data, to identify the molecular bases of HLBS disease. We will first focus on the transcriptional machinery controlling heart physiology and its disorders before exploring other HLBS-relevant tissues and disorders in collaboration with other TOPMed investigators. Our specific aims are: (1) Identifying the transcriptional machinery in the heart and other HLBS relevant tissues; and, (2) Connecting genomic variation in the transcriptional machinery to HLBS traits. Our approach will enable identification of the core molecular components that control HLBS tissues and how they are compromised in HLBS disorders.

正向遗传全基因组关联研究（GWAS）已经成功地绘制了数千个基因座调节心脏、肺、血液和睡眠（HLBS）的疾病，涉及广泛的序列变异在非编码基因组中。然而，它们的功能、作用机制以及它们如何影响疾病是不确定的。目前仍不清楚.为了解决这个新的和重要的GWAS瓶颈，我们使用功能基因组学启发的反向确定“转录机制”（转录因子（TF）、顺式调节元件 (CRE)靶基因）控制HLBS相关组织功能以及其中的DNA变体如何影响HLBS 疾病利用我们在复杂心血管疾病领域的长期专业知识和成功经验，和新的计算方法，我们最近开发的，我们提出了新的基因组学分析，用于精准医学的跨组学（TOPMed）计划表型及其全基因组序列，与公开的表观基因组学数据一起，以确定HLBS疾病的分子基础。我们将首先在探索其他心脏疾病之前，与其他TOPM研究者合作的HLBS相关组织和疾病。我们的具体目标是： (1)鉴定心脏和其他HLBS相关组织中的转录机制;以及（2）连接基因组变异的转录机制HLBS性状。我们的方法将能够识别控制HLBS组织的核心分子组分以及它们在HLBS疾病中如何受损。