Genetic Transmission of Components of the Human Gut Microbiome

描述（由申请人提供）：居住在人体中的微生物现在被视为我们生物学的一个组成部分，微生物组的可变性可以导致疾病易感性的差异。人类微生物组计划（HMP）被纳入NIH路线图优先事项，这突显了人们对人类微生物组相互作用这一新领域日益增长的兴趣。我们提出的研究将通过建立人类微生物组的遗传成分和阐明宿主基因型与肠道微生物组变异性之间的关系来补充和扩展HMP的目标。拟议的研究将试图量化微生物组组成中遗传的、个体间差异的大小。为了实现这一目标，我们将对TwinsUK项目中已有的全基因组SNP基因型数据进行分析，以确定微生物组组成的遗传决定因素。对于Specific Aim 1，我们将通过应用粪便样品的高通量Illumina测序来表征4,000对双胞胎的微生物组，为每个个体生成约300,000个16S rRNA基因序列。这些rRNA序列数据将编目和量化微生物群的个体间变异性，并产生微生物组物种组成的系统发育表示，从中提取出几个多样性指标。将在5个时间点取样双胞胎的一个子集，以评估微生物组组成的时间稳定性。对于Specific Aim 2，我们将通过确定宿主遗传控制下的多样性和特定分类群组成的措施来建立肠道微生物群的遗传力。全基因组SNP数据将用于估计每个异卵双胞胎（DZ）之间共享的基因组比例（大约在35%到65%之间变化）。我们将使用这种遗传身份（IBD）与微生物组指标共享的协方差来估计遗传方差成分，并提供每个微生物组属性可遗传的假设的检验。在Specific Aim 3中，我们将应用IBD和关联图谱来确定与肠道微生物组观察到的变化有关的人类基因组区域。在基因组的每个点上，将推断每个DZ双胞胎的局部IBD共享，并通过最大似然拟合定量遗传模型，以估计包含候选基因（例如，先天免疫基因/途径）的区域和基因组的每个局部区域的加性和显性方差成分。似然比检验将确定每个区域是否具有显著的QTL。此外，我们将通过相似性对微生物组进行聚类，并确定具有相似微生物组的双胞胎具有高水平IBD共享的人类基因组区域。这项研究的结果将用于建立人类基因组区域和微生物组组成之间的联系。这项研究的结果有可能揭示基本的人类宿主-微生物相互作用，可能适用于慢性炎症性疾病的预防和治疗。

DESCRIPTION (provided by applicant): The microbes that inhabit the human body are now viewed as an integral component of our biology, and microbiome variability can result in differences in predisposition to disease. The growing interest in this new field of human-microbiome interactions is underscored by the inclusion of the Human Microbiome Project (HMP) in the NIH RoadMap priorities. Our proposed research will complement and extend the goals of the HMP by establishing heritable components of the human microbiome and elucidating the relationship between host genotype and gut microbiome variability. The proposed research will attempt to quantify the magnitude of heritable, inter-individual differences in microbiome composition. To achieve this objective, we will pursue three specific aims in an analysis of genome-wide SNP genotype data already available from the TwinsUK project to identify genetic determinants of microbiome composition. For Specific Aim 1, we will characterize the microbiomes of 4,000 twin pairs through application of high-throughput Illumina sequencing of fecal samples to generate approximately 300,000 16S rRNA gene sequences for each individual. These rRNA sequence data will catalog and quantify inter-individual variability in microbiota and produce a phylogenetic representation of the microbiome species composition from which several diversity metrics will be distilled. A subset of twins will be sampled at 5 time points to assess temporal stability of microbiome composition. For Specific Aim 2, we will establish the heritability of the gut microbiota by identifying measures of diversity and specific taxon composition that are under host genetic control. The genome-wide SNP data will be used to estimate the proportion of the genome that is shared between each dizygotic (DZ) twin pair (which varies between about 35% and 65%). We will use the covariance of this Identity-by-Descent (IBD) sharing with the microbiome metrics to estimate genetic variance components and provide tests of the hypothesis that each microbiome attribute is heritable. For Specific Aim 3, we will apply IBD and association mapping to identify regions of the human genome responsible for the observed variation in gut microbiomes. At each point along the genome the local IBD sharing for each DZ twin-pair will be inferred, and quantitative genetic models will be fitted by maximum likelihood to estimate additive and dominance variance components for regions containing candidate genes (e.g., innate immunity genes/pathways) and for each local region of the genome. Likelihood ratio tests will determine whether each region has a significant QTL. In addition, we will cluster microbiomes by similarity and identify regions of the human genome with high levels of IBD sharing for twin pairs with similar microbiomes. The results of this research will be used to establish links between regions of the human genome and composition of the microbiome. The results of this study have the potential to reveal fundamental human host- microbe interactions that may be applicable to the prevention and treatment of chronic inflammatory diseases.