Genetic control over the gut microbiome composition

对肠道微生物组组成的遗传控制

• 批准号: 7833677
• 负责人: ANDREW K BENSON
• 金额: $ 49.77万
• 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 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7833677
• 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(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。人类胃肠道被一群与宿主密切互动的微生物(肠道微生物群)占据。肠道微生物群与宿主代谢和免疫功能之间的联系是复杂和重要的；肠道微生物群获取或最终组成的异常被认为是复杂的NIDDK疾病的重要易感因素，如肥胖、炎症性肠病和以后的胃癌。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，既受环境因素(机会接触、饮食)和一些宿主遗传因素的影响，如那些影响粘膜免疫的因素。同样，那些影响肠道微生物组组成的宿主遗传基因座，特别是其已知的致病因素部分，可能会影响一个人的整体疾病易感性。通过一整套协同作用的特定目标，我们将探索宿主对小鼠肠道微生物群组成的遗传控制。我们这项研究的基本原理是，它提供了一种新的手段，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一个多基因性状，控制其组成的宿主基因可以通过高分辨率的数量性状基因座(QTL)定位来识别。利用深度焦磷酸测序将肠道微生物组的单个类群的相对丰度量化为“宿主性状”，我们的初步数据清楚地表明，从两个常见的小鼠品系C57BL/6J和HR(来源于ICR)的F4杂交作图群体中，通过肠道微生物组组成性状与SNP标记的共分离模式，可以成功地在200只小鼠中定位到强QTL。我们目前的目标是系统地建立小鼠数量遗传模型，作为一种全面定位影响微生物组组成的QTL的方法。这将通过对日益复杂和多样化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，以包括该种群中的所有800只小鼠。在这个队列中确定的肠道微生物组QTL随后将使用来自同一来源的F10杂交群体进行精细定位。其次，我们将扩大我们的遗传基础，通过对~40个初级小鼠物候组数据库近交系进行表型鉴定和应用基于单倍型的QTL关联作图。第三，我们将对合作杂交(CC)进行研究，这是一大批重组近交系小鼠，由包括野生种质在内的8个高度分化的自交系杂交而成。CC是唯一一种具有高度和统一的全基因组变异的哺乳动物资源，有效地在一个庞大的、不同种类的种群中随机分布，这也支持了跨环境和生物条件以及随着时间的推移的整合。CC捕捉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来探索基因组搜索空间，以一种人类不可能的方式来开发特定的、高置信度的模型，以便在未来的小鼠验证和新的人类研究中进行测试。我们的创新实验充分利用了强大的遗传资源种群和广泛的专业知识，包括创建和评估大量实验小鼠、高密度SNP数据分析、QTL作图和统计基因组学、复杂微生物群的焦磷酸测序分析、系统发育分析以及大型复杂数据集的分析。这项提案中代表的团队已经建立了令人印象深刻的合作，以创造一种新的实验方法和有利的研究环境。 公共卫生相关性：这项研究将帮助我们通过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，更好地识别与NIDDK疾病有关的基因。对NIDDK疾病遗传学的更全面了解将导致新的更好的治疗方法，并提高我们筛查和预防肥胖症、IBD和某些形式癌症等负担沉重的疾病的能力。这项研究将通过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，帮助我们更好地识别与NIDDK疾病有关的基因。对NIDDK疾病遗传学的更全面了解将导致新的更好的治疗方法，并提高我们筛查和预防肥胖症、IBD和某些形式癌症等负担沉重的疾病的能力。