Population Genomics of Host-Microbiome Interactions

寄主-微生物组相互作用的群体基因组学 寄生在人体内的微生物群落的组成有很大的差异。 在个体和种群中，这种变异与许多寄主特征和 疾病。了解影响这种变异的因素，以及这种变异的机制 影响宿主性状，是人类疾病研究的中心目标。尽管其中的一些变化 微生物群是由宿主遗传控制的，我们对控制微生物群的基因组因素知之甚少 人与微生物群之间的相互作用及其对复杂人类疾病的影响。解开纠缠 环境对微生物组的遗传影响是具有挑战性的，微生物组通常在 单个时间点，这不能解释微生物组的纵向变化。此外，我们的大多数人 关于宿主-微生物组相互作用的知识由相互关联组成，我们不知道如何 微生物群落组成的个体间和种群间的差异影响寄主基因的调控。 我的实验室的研究旨在解决知识中的这些关键差距。我实验室的研究是基于 微生物组可以被认为是数量性状的假设，因此我们可以直接定位宿主 控制微生物组变异的基因组因素，以及识别单个寄主基因和 受微生物群调控的途径。我的实验室未来五年的研究计划是 为了回答关于宿主-微生物组相互作用的基因组基础的基本问题，通过三个广泛的， 补充项目领域，旨在：(1)开发计算技术，将微生物组和 宿主基因组数据，并应用这些方法来实现对宿主微生物组的系统级理解 跨人群和疾病状态的交互作用；(2)表征功能成分的遗传性 微生物组(微生物基因、菌株和途径)和评估终身纵向影响 灵长类动物模型系统中寄主生理的微生物组动力学；以及(3)使用新的体外和体外实验 了解微生物群系中个体间和种群间变异对 宿主基因调控，并描述潜在的调控机制。 拟议的研究计划将提供系统级别的观点，了解分子之间的相互作用。 宿主基因和肠道中的微生物因子跨越人群、环境和疾病；特征 微生物组纵向动态以及基因、途径和菌株如何受宿主控制 以及对微生物调节宿主基因的机制的描述。这些结果将 改变我们对人类基因组和微生物组之间相互作用的理解，解释这一点 相互作用影响疾病，并使基于微生物组的治疗和诊断技术的发展成为可能 改善人类健康。

Population Genomics of Host-Microbiome Interactions There is wide variation in the composition of the microbial communities that colonize the human body across individuals and populations, and this variation has been associated with numerous host traits and diseases. Understanding the factors that influence this variation, and the mechanism by which this variation affects host traits, is of central goal in human disease research. Although some of the variation in the microbiome is controlled by host genetics, we know very little about the genomic factors that control the interaction between humans and the microbiome and their effect on complex human disease. Disentangling genetic from environmental effects on the microbiome is challenging, and the microbiome is usually profiled in a single time point, which doesn’t account for microbiome longitudinal variation. Moreover, most of our knowledge on host-microbiome interactions consists of correlational associations, and we do not know how inter-individual and inter-population variation in microbiome composition affects host gene regulation. My laboratory’s research aims to address these critical gaps in knowledge. Research in my lab is based on the hypothesis that the microbiome can be considered a quantitative trait, and thus we can directly map host genomic factors controlling the variation in the microbiome, as well as identify individual host genes and pathways that are regulated by the microbiome. My lab’s research program for the next five years is designed to answer fundamental questions about the genomic basis of host-microbiome interactions via three broad, complementary Project Areas, aiming to: (1) develop computational techniques to integrate microbiome and host genomic data, and apply these methods to achieve a systems-level understanding of host-microbiome interactions across populations and disease states; (2) characterize the heritability of functional components of the microbiome (microbial genes, strains, and pathways) and assess the effect of life-long longitudinal microbiome dynamics on host physiology in a primate model system; and (3) use novel in-vitro and ex-vivo systems to understand the causal effect of inter-individual and inter-population variation in the microbiome on host gene regulation and describe the underlying regulatory mechanism. The proposed research program will provide a systems-level view of the molecular interactions between host genes and microbial factors in the gut across populations, environments, and diseases; a characterization of how microbiome longitudinal dynamics, as well as genes, pathways, and strains are controlled by host genetic; and a description of the mechanism with which microbes regulate host genes. These results would transform our understanding of the interplay between human genomics and the microbiome, explain how this interaction affects disease, and enable development of microbiome-based therapeutics and diagnostics that improve human health.