Systems-level transcriptomic analyses to Identify mouse models of asthma

系统级转录组分析识别哮喘小鼠模型

• 批准号: 9120405
• 负责人: Samir Kelada
• 金额: $ 53.39万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2019-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9120405
• 关键词: Acute; Address; Affect; Alleles; Allergens; Allergic rhinitis; Asthma; Binding Sites; Bioinformatics; Breathing; Chronic; Coupled; Data; Data Set; Development; Disease; Disease model; Epithelial; Exhibits; Feedback; Gene Cluster; Gene Expression; Gene Expression Profile; Gene Expression Regulation; Gene Targeting; Genes; Genetic; Genetic Variation; Genomics; Goals; Grant; Health; Health Care Costs; High Prevalence; Human; Knock-out; Laboratories; Lung; Measures; Meta-Analysis; Methods; MicroRNAs; Modeling; Molecular; Mouse Strains; Mucins; Mus; NIH Program Announcements; Onset of illness; Pathway interactions; Pattern; Phenotype; Population; Prevalence; Prevention strategy; Process; Quality of life; Regulator Genes; Research Personnel; Site; System; Testing; Time; Transcriptional Regulation; Validation; Western World; airway epithelium; airway hyperresponsiveness; airway inflammation; allergic airway disease; base; comparative; design; differential expression; disease phenotype; disorder prevention; disorder subtype; drug discovery; genetic resource; human data; human disease; in vivo; innovation; knock-down; knockout gene; man; mouse model; new therapeutic target; novel; novel therapeutics; predictive modeling; prevent; response; skills; therapeutic target; transcription factor; transcriptome; transcriptome sequencing; transcriptomics; treatment strategy

 DESCRIPTION (provided by applicant): The high prevalence of allergic airway diseases (AADs) including asthma and allergic rhinitis make identifying new disease prevention and treatment strategies a priority. Recent studies have shown that gene expression in airway epithelia is associated with AAD and may underlie different AAD sub-types. With few exceptions, the key transcriptional regulators of epithelial gene expression in AAD are unknown. Their identification represents an important step in the development of novel therapeutic strategies. The identification of novel therapeutic targets has also been hindered by the lack of validated mouse models for AAD (in particular, sub-types of asthma). We hypothesize that we can identify mouse models of AAD that more closely mimic human AAD sub- types than currently exists using conserved patterns of gene expression as decision criteria. Further, we hypothesize that these new models can be used to identify and test novel disease targets. In Aim 1, we will build predictive models of transcriptional regulation in AAD in which master regulators of gene expression, namely transcription factors (TFs) and microRNAs (miRNAs), are coupled to their target genes. We will first perform a meta-analysis of six transcriptomic studies of human AAD (N = 218 subjects: 118 asthma cases, 26 allergic rhinitis cases, and 74 controls) to identify genes consistently altered in AAD and which genes distinguish AAD sub-types. We will then identify putative master regulators of the differentially expressed genes (including subsets that are co-expressed) using gene set enrichment analysis for regulatory motifs (transcription factor binding sites and miRNA target sites). In Aim 2, we will identify new strains of mice from the Collaborative Cross (CC) population, which features enhanced genetic diversity compared to existing mouse genetics resources, that better mimic human AAD sub-types. We will phenotype 40 CC strains for hallmark AAD phenotypes in response to acute and chronic allergen exposure, and measure lung gene expression by RNA-sequencing. Using an innovative statistical approach of the RNA-seq data, we will identify which CC strains exhibit patterns of gene expression most akin to human AAD subtypes. At the same time, we will conduct gene set enrichment analysis of differentially expressed (and co-expressed) genes to identify key TFs and miRNAs that are shared between human and mouse. In Aim 3, we conduct the validation component of the grant. We will test whether novel candidate master regulators that are conserved between mouse and man (identified in Aims 1 and 2) represent new AAD therapeutic targets. We will perturb two candidate master regulators in vivo using gene knockdown and gene knockout approaches in mice. The effect of these perturbations will be evaluated in acute and chronic allergen models to test whether altering the master regulator can affect AAD onset and/or modify established AAD. Thus in total we will (1) identify conserved master regulators of AAD phenotypes, (2) establish new mouse models of AAD that better mimic human disease, and (3) evaluate whether master regulators of gene expression represent novel drug targets.

 描述（由申请人提供）：包括哮喘和过敏性鼻炎在内的过敏性气道疾病（AAD）的高患病率使确定新的疾病预防和治疗策略成为优先事项。近年来的研究表明，气道上皮细胞基因表达与AAD相关，并可能是AAD不同亚型的基础。除了少数例外，AAD中上皮基因表达的关键转录调节因子尚不清楚。它们的鉴定代表了新型治疗策略开发的重要一步。由于缺乏经验证的AAD小鼠模型（特别是哮喘亚型），新治疗靶点的鉴定也受到阻碍。我们假设，我们可以确定小鼠模型的AAD，更接近模仿人类AAD亚型比目前存在的使用保守模式的基因表达作为决策标准。此外，我们假设这些新模型可用于识别和测试新的疾病靶点。在目标1中，我们将建立AAD中转录调控的预测模型，其中基因表达的主调节因子，即转录因子（TF）和microRNA（miRNA）与其靶基因偶联。我们将首先对6项人类AAD转录组学研究（N = 218例受试者：118例哮喘病例，26例过敏性鼻炎病例和74例对照）进行荟萃分析，以确定AAD中持续改变的基因以及哪些基因可区分AAD亚型。然后，我们将使用调控基序（转录因子结合位点和miRNA靶位点）的基因集富集分析来鉴定差异表达基因（包括共表达的子集）的推定主调控因子。在目标2中，我们将识别新菌株 来自协作杂交（CC）种群的小鼠，与现有的小鼠遗传资源相比，其具有增强的遗传多样性，更好地模拟人类AAD亚型。我们将对40株CC菌株进行表型分析，以确定急性和慢性过敏原暴露后的标志性AAD表型，并通过RNA测序测量肺基因表达。使用RNA-seq数据的创新统计方法，我们将确定哪些CC菌株表现出与人类AAD亚型最相似的基因表达模式。同时，我们将对差异表达（和共表达）的基因进行基因集富集分析，以确定人和小鼠之间共享的关键TF和miRNA。在目标3中，我们进行赠款的验证部分。我们将测试在小鼠和人之间保守的新型候选主调节因子（在目的1和2中鉴定）是否代表新的AAD治疗靶点。我们将在小鼠体内使用基因敲低和基因敲除方法干扰两个候选主调节因子。将在急性和慢性过敏原模型中评价这些扰动的影响，以检测改变主调节因子是否会影响AAD发作和/或改变已确立的AAD。因此，总的来说，我们将（1）确定AAD表型的保守主调节因子，（2）建立新的AAD小鼠模型，更好地模拟人类疾病，（3）评估基因表达的主调节因子是否代表新的药物靶点。