Gene Expression and Regulatory Networks in Human Leukocytes

人类白细胞的基因表达和调控网络

• 批准号: 7854791
• 负责人: CHRISTOPHE O. BENOIST
• 金额: $ 409.77万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7854791
• 关键词: Adverse event; Affect; African American; Age; Aging; Architecture; Area; Asians; Benchmarking; Biological Markers; Blood; Blood Cells; CD4 Positive T Lymphocytes; Cell Lineage; Cells; Cereals; Chromosome Mapping; Clinical Trials; Cluster Analysis; Communities; Complement; Complex; Computational Biology; Computational algorithm; Computer Analysis; DNA; DNA Microarray Chip; Data; Data Analyses; Data Set; Dendritic Cells; Diagnostic; Disease; Disease Pathway; Dissection; Engineering; Environment; European; Exons; Flow Cytometry; Functional RNA; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Genes; Genetic; Genetic Structures; Genetic Variation; Genome; Genomics; Genotype; Hand; Health; Hospitals; Human; Human Genetics; Human Genome; Immune; Immunologist; Immunophenotyping; Individual; Inflammatory; Institutes; International; Internet; Knowledge; Leukocytes; Ligands; Lymphocyte; Maps; Messenger RNA; Metadata; MicroRNAs; Molecular Profiling; Monitor; Mus; Myeloid Cells; Pathogenesis; Pathway interactions; Pattern; Phenotype; Population; Predisposition; Procedures; Protocols documentation; RNA; RNA Splicing; Resolution; Resources; Sampling; T-Lymphocyte; Techniques; Technology; Time; Transcript; Treatment Efficacy; Variant; Woman; Work; base; cell type; cohort; cost; cytokine; density; genome-wide; healthy volunteer; heuristics; interdisciplinary collaboration; monocyte; prognostic; reconstruction; repository; research study; response; sample collection; tool; volunteer; young adult

DESCRIPTION (provided by applicant): Profiling of gene expression with microarrays holds great potential for human health, for illuminating disease pathways or providing biomarkers to monitor disease or its resolution. Using high-throughput approaches for genotyping, immunophenotyping and gene expression analysis, the project will examine the basis for the control of gene expression in human immune cells, and how it is influenced by natural genetic variation or aging. In practice, the project will combine several cross-informative approaches: 1) Building on the established sample/data pipelines and robust protocols of the Immunological Genome (ImmGen) project, and on established cohorts of ethnically diverse healthy volunteers at hand, microarray techniques will be used to generate whole-genome expression profiles from purified na¿ve CD4+ lymphocytes and monocytes from 600 healthy volunteers. A dense genetic map will be established for all donors. The results will elucidate how variation in the human genome affects the expression of immune genes, of key importance in understanding gene variants that bring susceptibility to immune or inflammatory disease. Computational analysis of these rich data will allow the reconstruction of regulatory connections between genes, helping to establish general modules and those specific of a given immune cell type. These data will be complemented by an orthogonal datagroup, generated from a restricted subset of 10 individuals, in which we will profile a larger set of 28 carefully delineated cell populations that exist in human blood. This work will also benefit from powerful interspecies comparison with similar experiments being performed in mice by ImmGen. 2) In addition, RNA from the same set of 28 defined cell populations will be probed with microarrays that explore other aspects of the transcriptome: i) microRNAs and other non-coding RNAs; ii) exon or splice junction arrays that will establish a map of differential splicing in human blood leukocyte. 3) The composition and reactivity of blood cells from the same donors will be established at the time of sample collection using high-throughput flow cytometry, correlating immune phenotypes with gene expression and genetic variation. 4) Genetic variability conditions the baseline levels of gene expression, but also the responsiveness to activating challenges. With samples from the same donors, Nanostring technology for transcript counting will be used to analyze the transcriptional response of defined gene sets, representing response signatures of T or dendritic cells, for a fine-grained dissection of responses to different triggers (different bacterial ligands for dendritic cells, different cytokine environment for T cells). In keeping with the resource aspect of this project, all data and interpretations will be made publicly available rapidly upon curation, allowing public querying and browsing of the data, by using and evolving the existing web architectures of the ImmGen project, of the Broad Institute, and of international repositories. RELEVANCE: Exploration with DNA chips of the genome's expression microarrays holds great potential for human health, to better understand disease and to serve as diagnostic tools. Using a combination of high-throughput genomic techniques and computational biology, we will perform a broad exploration of gene expression in human blood cells across groups of African-American, Asian and European ancestry, asking how these profiles are affected by genetic variation or by age. These results will provide an invaluable reference benchmark for the interpretation of genetic and immunological studies.

描述（通过应用提供）：基因表达与微阵列的分析具有人类健康的巨大潜力，照明疾病途径或提供生物标志物来监测疾病或其解决方案。使用高通量方法进行基因分型，免疫表型和基因表达分析，该项目将研究人类免疫细胞中基因表达的控制的基础，以及它如何受到自然遗传变异或衰老的影响。实际上，该项目将结合几种交叉信息： 1）建立在既定的样本/数据管道和免疫基因组项目（IMMGEN）项目的鲁棒方案上，并在手头的既定种族多样性健康志愿者的同类群体上建立，微阵列技术将用于从纯化的NA？ve cd4+ CD4+淋巴细胞和单型健康的健康型健康的纯化NAOCENOME表达概况中产生全基因组表达曲线。将为所有捐助者建立密集的遗传图。结果将阐明人类基因组中的变异如何影响免疫基因的表达，这对于理解基因变异的关键性具有关键，这些基因变异具有对免疫或炎症性疾病的敏感性。这些丰富数据的计算分析将允许重建基因之间的调节连接，从而有助于建立一般模块和特定的给定免疫器类型的模块。这些数据将由一个正交数据集团完成，该数据段是由10个个体的受限子集生成的，其中我们将介绍人类血液中存在的28个较大的28个精心描绘的细胞群体。这项工作还将受益于强大的种间比较与Immgen在小鼠中进行的类似实验的比较。 2）此外，将使用探索转录组其他方面的微阵列探测同一组定义的细胞种群的RNA：i）microRNA和其他非编码RNA； ii）外显子或剪接连接阵列将在人类白细胞中建立差异图的图。 3）在采集样品时，将使用高通量流式细胞仪建立来自同一供体的血细胞的组成和反应性，将免疫表型与基因表达和遗传变异相关联。 4）遗传变异条件条件基因表达的基线水平，也适用于激活挑战的反应。使用来自同一供体的样品，用于转录本计数的纳米弦技术将用于分析定义基因组的转录响应，代表T或树突状细胞的反应特征，以对不同触发因素的响应进行细粒度的解剖（对树突状细胞的不同细菌的不同细胞）的响应，对树突状细胞，不同的细胞基细胞）。 为了与该项目的资源方面保持一致，所有数据和解释都将公开进行 策划后迅速获得，可以通过使用和发展Immgen项目的现有Web架构，广泛研究所和国际存储库，从而允许公开查询和浏览数据。 相关性：与基因组表达微阵列的DNA芯片的探索具有巨大的人类健康潜力，可以更好地理解疾病并充当诊断工具。使用高通量基因组技术和计算生物学的结合，我们将对非裔美国人，亚裔和欧洲血统群体中人类血细胞中的基因表达进行广泛的探索，询问这些特征如何受遗传变异或按年龄的影响。这些结果将为解释遗传学和免疫学研究的解释提供宝贵的参考基准。