Genetic control over the gut microbiome composition

对肠道微生物组组成的遗传控制

• 批准号: 7938096
• 负责人: ANDREW K BENSON
• 金额: $ 50万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-28 至 2012-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7938096
• 关键词: Address; Affect; American; Animals; Area; Biological; Collaborations; Complex; Data; Data Set; Databases; Diet; Disease; Ecology; Environment; Environment and Public Health; Environmental Risk Factor; Future; Gastrointestinal tract structure; Generations; Genes; Genetic; Genetic Models; Genomics; Genotype; Haplotypes; Health Expenditures; Human; Immune; Inbred Mouse; Individual; Inflammatory Bowel Diseases; Lead; Life; Low income; Malignant Neoplasms; Maps; Metabolic; Microbe; Minority; Modeling; Mouse Strains; Mucosal Immunity; Mus; National Institute of Diabetes and Digestive and Kidney Diseases; Obesity; Pattern; Phenotype; Phylogenetic Analysis; Polygenic Traits; Population; Population Heterogeneity; Predisposition; Probability; Public Health; Quantitative Genetics; Quantitative Trait Loci; Randomized; Reading; Recombinants; Relative (related person); Research; Resolution; Resources; Role; Series; System; Taxon; Taxonomy; Technology; Testing; Time; Tissues; Validation; Variant; Work; base; cohort; density; forging; genetic resource; genome-wide; immune function; improved; innovation; malignant stomach neoplasm; mammalian genome; microbial; microbiome; mouse genome; phenome; prevent; public health relevance; research study; segregation; success; trait

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (08): Genomics and specific Challenge Topic, 04-DK-101: Role of the Human Gut Microbiome in NIDDK Diseases. The human gastrointestinal tract is colonized by a climax population of microbes (the gut microbiome) that interacts intimately with its host. Linkages between the gut microbiome and host metabolic and immune functions are complex and vital; aberrations in the acquisition or ultimate composition of the gut microbiome are believed to be an important predisposition factor in complex NIDDK diseases such as obesity, inflammatory bowel disease, and gastric cancers later in life. Like these multifactorial diseases, composition of the gut microbiome is in itself a complex trait, affected by both environmental factors (chance exposure, diet) and a number of host genetic factors such as those influencing mucosal immunity. Similarly, those host genetic loci that affect composition of the gut microbiome, especially those portions of it that are known to be factors in disease, are likely to contribute to one's overall predisposition to disease. With an integrated set of synergistic specific aims, we will explore the host genetic control over gut microbiome composition in mice. Our rationale for this research is that it provides a new means for identifying disease predisposition loci through the effects of these loci on composition of the gut microbiome. Our working hypothesis is that composition of the gut microbiome is a polygenic trait and that host genes controlling its composition can be identified by high- resolution quantitative trait loci (QTL) mapping. Using deep pyrosequencing to quantify the relative abundance of individual taxa of the gut microbiome as "host traits", our preliminary data show clearly that strong QTL can be successfully identified by co-segregation patterns of gut microbiome composition traits with SNP markers in 200 mice from an F4 intercross mapping population between two common mouse strains, C57BL/6J and HR (derived from ICR). Our current objective is to establish mouse quantitative genetic models systematically as an approach to comprehensively map QTL affecting composition of the microbiome. This will be accomplished through a series of analyses and association studies in mouse populations with increasing complexity and diversity. First, we will expand our C57 x HR F4 analysis to include all 800 mice in this population. Gut microbiome QTL identified in this cohort will then be fine-mapped using an F10 intercross population from the same origin. Second, we will expand our genetic base by phenotyping the ~40 primary Mouse Phenome Database inbred lines and applying haplotype-based QTL association mapping. And third, we will take our studies into the Collaborative Cross (CC), a large panel of recombinant inbred mouse lines derived from intercrossing of eight highly divergent inbred lines including wild germplasm. The CC is the only mammalian resource that has high and uniform genome-wide variation effectively randomized across a large, heterogeneous population which also supports integration across environmental and biological conditions and over time. The CC captures the complexity of the mammalian genome and permits modeling of complex systems and interactions that influence disease. We will use the CC to explore the genomic search space in a manner impossible in humans to develop specific, high confidence models to be tested in future mouse validation and new human studies. Our innovative experiments capitalize on powerful genetic resource populations and an extensive array of expertise in creating and evaluating large populations of experimental mice, analysis of high-density SNP data, QTL mapping and statistical genomics, pyrosequencing analysis of complex microbiomes, phylogenetic analysis, and analysis of large complex data sets. The team represented in this proposal has forged impressive collaborations to create a new experimental approach and favorable research environments. PUBLIC HEALTH RELEVANCE: This research will help us better identify genes contributing to NIDDK diseases through their effects on composition of the gut microbiome, and specifically, aberrant patterns of colonization. A more complete understanding of the genetics of NIDDK diseases will lead to new and better treatments and improve our ability to screen for and prevent such burdensome conditions as obesity, IBD and some forms of cancer. This research will help us better identify genes contributing to NIDDK diseases through their effects on composition of the gut microbiome, and specifically, on aberrant patterns of colonization. A more complete understanding of the genetics of NIDDK diseases will lead to new and better treatments and improve our ability to screen for and prevent such burdensome conditions as obesity, IBD and some forms of cancer.

描述（由申请人提供）：本申请涉及广泛的挑战领域（08）：基因组学和特定的挑战主题，04-DK-101：人类肠道微生物组在NIDDK疾病中的作用。人类胃肠道由与其宿主密切相互作用的微生物（肠道微生物组）的高潮群体定殖。肠道微生物组与宿主代谢和免疫功能之间的联系是复杂和重要的;肠道微生物组的获取或最终组成的异常被认为是复杂NIDDK疾病（如肥胖症，炎症性肠病和胃癌）的重要易感因素。与这些多因素疾病一样，肠道微生物组的组成本身是一个复杂的特征，受环境因素（偶然暴露，饮食）和许多宿主遗传因素（如影响粘膜免疫的因素）的影响。同样，那些影响肠道微生物组组成的宿主遗传基因座，特别是已知是疾病因素的那些部分，可能有助于一个人对疾病的整体易感性。通过一套综合的协同特定目标，我们将探索宿主对小鼠肠道微生物组组成的遗传控制。我们进行这项研究的理由是，它提供了一种新的方法，通过这些基因座对肠道微生物组组成的影响来识别疾病易感基因座。我们的工作假设是肠道微生物组的组成是多基因性状，并且控制其组成的宿主基因可以通过高分辨率数量性状基因座（QTL）作图来鉴定。使用深度焦磷酸测序来量化作为“宿主性状”的肠道微生物组的个体分类群的相对丰度，我们的初步数据清楚地显示，可以通过来自两种常见小鼠品系C57 BL/6 J和HR（源自ICR）之间的F4互交作图群体的200只小鼠中的肠道微生物组组成性状与SNP标记的共分离模式成功地鉴定强QTL。我们目前的目标是系统地建立小鼠数量遗传模型，作为全面定位影响微生物组组成的QTL的方法。这将通过对复杂性和多样性不断增加的小鼠种群进行一系列分析和关联研究来实现。首先，我们将扩展我们的C57 x HR F4分析，以包括该群体中的所有800只小鼠。然后将使用来自相同起源的F10互交群体对在该群组中鉴定的肠道微生物组QTL进行精细作图。其次，我们将通过对~40个主要小鼠表型数据库近交系进行表型分析和应用基于单倍型的QTL关联作图来扩大我们的遗传基础。第三，我们将把我们的研究到协作杂交（CC），一个大面板的重组近交系小鼠品系来自八个高度不同的近交系，包括野生种质杂交。CC是唯一的哺乳动物资源，具有高和均匀的全基因组变异，有效地随机分布在一个大的，异质的人口，也支持跨环境和生物条件和随着时间的推移整合。CC捕获了哺乳动物基因组的复杂性，并允许对影响疾病的复杂系统和相互作用进行建模。我们将使用CC以人类不可能的方式探索基因组搜索空间，以开发特定的，高置信度的模型，用于未来的小鼠验证和新的人类研究。我们的创新实验利用了强大的遗传资源群体和广泛的专业知识，包括创建和评估大量实验小鼠群体，分析高密度SNP数据，QTL定位和统计基因组学，复杂微生物组的焦磷酸测序分析，系统发育分析和大型复杂数据集的分析。该提案中所代表的团队已经建立了令人印象深刻的合作，以创造新的实验方法和有利的研究环境。 公共卫生关系：这项研究将帮助我们更好地识别导致NIDDK疾病的基因，通过它们对肠道微生物组组成的影响，特别是异常的定植模式。更全面地了解NIDDK疾病的遗传学将导致新的和更好的治疗方法，并提高我们筛查和预防肥胖，IBD和某些形式的癌症等负担性疾病的能力。这项研究将帮助我们更好地识别导致NIDDK疾病的基因，通过它们对肠道微生物组组成的影响，特别是对异常定植模式的影响。更全面地了解NIDDK疾病的遗传学将导致新的和更好的治疗方法，并提高我们筛查和预防肥胖，IBD和某些形式的癌症等负担性疾病的能力。