The genetic basis of cross-tissue protein expression variability in humans

人类跨组织蛋白表达变异的遗传基础

• 批准号: 8853310
• 负责人: BARBARA E STRANGER
• 金额: $ 40万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2017-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8853310
• 关键词: Address; Antibodies; Architecture; Attention; Biological; Biology; Buffers; Cells; Clinical; Collection; Communities; Complement; Complex; Core Facility; DNA; Data; Data Analyses; Data Collection; Data Set; Disease; Ensure; Gene Expression Profile; Generations; Genes; Genetic; Genetic Transcription; Genetic Translation; Genetic Variation; Genetic study; Genome; Genomics; Genotype; Health; High Performance Computing; Human; Individual; Individual Differences; Knowledge; Left ventricular structure; Link; Lung; Maps; Measurement; Measures; Messenger RNA; Molecular Profiling; Pathway interactions; Phase; Play; Population; Post-Translational Protein Processing; Process; Protein Array; Protein Biosynthesis; Proteins; Proteome; Proteomics; Protocols documentation; Quantitative Trait Loci; RNA; RNA Sequences; Reagent; Research; Research Personnel; Resources; Role; Sampling; Signal Transduction; Signaling Protein; Skeletal Muscle; Specificity; Structure of tibial nerve; System; Thyroid Gland; Time; Tissue Sample; Tissues; Transcript; Translations; Variant; base; cohort; disorder risk; functional genomics; genetic risk factor; genetic variant; genome annotation; genome-wide; genomic variation; human disease; human tissue; interest; mRNA Expression; novel; population based; programs; protein expression; trait; transcription factor; transcriptome sequencing

DESCRIPTION (provided by applicant): Human functional population genomics has great potential to increase our understanding of biological mechanisms that link genetics with complex human disease. Many genetic variants associated with human disease influence mRNA levels, and, it is assumed, protein expression variation. We believe that collection of proteomic data from samples of the Genotype-Tissue Expression (GTEx) program will complement other ongoing genomic data collection efforts. Through direct measurement of protein levels across individuals and tissues, we will have the ability to further validate functionality of genome-transcriptome relationships while simultaneously characterizing novel genome-proteome relationships and their relationship to transcriptome biology, and at the same time characterizing the tissue-context specificity of these relationships. Knowledge of the unique relationships between genomes with proteomes and transcriptomes will allow us and others to subsequently explore novel hypotheses related to the genetic components of common diseases. We will characterize five tissues of the GTEx samples in a high-throughput, robust manner for protein levels in a population-based framework, and will analyze these data in the context of additional GTEx genomics datasets, and publically available genome annotation. The research will build upon existing resources, including a core proteomics facility, robust analytic pipelines, high performance computing, but more importantly on our long- standing research interests in human population genomics, discovery and characterization of regulatory variation, and genome studies of complex diseases and traits in humans. Thus, our specific aims are: 1) to characterize protein expression profiles across five human tissues to discover cross-tissue and tissue-specific protein expression variation for individual proteins and pathways; 2) to integrate the relationships between variation in genetic, transcriptome and proteome profiles; and 3) to use systems and network approaches for a better understanding of the organization of the proteome and transcriptome, including regulatory circuits within and across tissues. All data and results produced through this project will be made publicly available immediately for use by the larger scientific community.

描述（由申请人提供）：人类功能群体基因组学具有巨大的潜力，可以增加我们对将遗传学与复杂人类疾病联系起来的生物学机制的理解。许多与人类疾病相关的遗传变异会影响mRNA水平，并被认为影响蛋白质表达变异。我们相信，从基因型-组织表达（GTEx）项目样本中收集蛋白质组学数据将补充其他正在进行的基因组数据收集工作。通过直接测量个体和组织中的蛋白质水平，我们将有能力进一步验证基因组-转录组关系的功能，同时表征新的基因组-蛋白质组关系及其与转录组生物学的关系，同时表征这些关系的组织-背景特异性。基因组与蛋白质组和转录组之间的独特关系的知识将使我们和其他人随后探索与常见疾病的遗传成分相关的新假设。我们将在基于群体的框架中以高通量、稳健的方式表征GTEx样品的5个组织的蛋白质水平，并将在其他GTEx基因组学数据集和公开可用的基因组注释的背景下分析这些数据。这项研究将建立在现有资源的基础上，包括一个核心的蛋白质组学设施，强大的分析管道，高性能计算，但更重要的是，我们长期以来对人类群体基因组学的研究兴趣，调控变异的发现和表征，以及人类复杂疾病和特征的基因组研究。因此，我们的具体目标是：1)表征五种人体组织中的蛋白质表达谱，以发现单个蛋白质和途径的跨组织和组织特异性蛋白质表达变异；2)整合遗传、转录组和蛋白质组谱变异之间的关系；3)使用系统和网络方法来更好地理解蛋白质组和转录组的组织，包括组织内和组织间的调节回路。通过该项目产生的所有数据和结果将立即公开，供更大的科学界使用。