Integration of Genomics and the Environment

 描述(申请人提供)：环境可能是人类疾病的主要因素，但在全基因组遗传学方法中，它的影响在很大程度上被忽略了。在这次CEGS中，我们将正面讨论环境影响基因组功能的机制，重点关注两个与人类健康高度相关的极其重要的暴露：饮食及其与代谢性疾病和癌症的关系；以及与神经精神疾病相关的压力。这需要几乎完全控制实验系统，而这在人类身上是做不到的。我们的第一个目标是建立一个新的了解基因-环境相互作用(GxE)的基础性实验小鼠模型。我们将用三种控制良好的饮食--西方饮食、地中海饮食、生酮饮食--对遗传异质性的协作杂交小鼠群体进行杂交，并测量代表新陈代谢和心血管疾病的器官系统的表型。我们还将确定饮食对偶氮甲烷诱导的结肠肿瘤的影响，以及压力对与神经精神疾病相关的表型的影响。我们将把这些分析与全基因组亚硫酸盐测序、染色质可及性分析以及目标组织包括肝脏、脂肪组织、结肠、海马体、前额叶皮质和血液的转录组相结合，测量环境、基因组、表观基因组和转录组之间在确定表型时信息的性质和流动。我们的第二个目标是开发新的统计方法以及一个新的数学框架来处理遗传学、表观遗传学和暴露之间的相互作用，这将使我们能够对信息如何在这三个领域之间传递以最终塑造表型进行建模。这些方法包括因果推理检验，基因不连续的基因-表观类型关系分析，以及基于统计物理和信息论基本概念的新的随机方法。我们的第三个目标是在幼稚动物和高度相关的人类流行病学队列中进行复制：针对饮食暴露和代谢紊乱的DWH和ALSPAC；针对饮食和结肠癌的NHSII和EPIC；以及针对压力和行为特征的ALSPAC和PIRC。我们的第四个目标是开发和发布新的测量、分析和计算技术，用于GxE的全面基因组分析。这些包括新的生物资源和软件包，以及生化、细胞和计算工具，以测试和改进来自其他目标的模型和结论，并对基因组学社区广泛使用，包括：用于确定长期GxE关系的单个或多个标记的分析；基因表达和表观遗传修饰的单细胞和原位分析；以及包括大数据集的超快比对在内的新的计算方法。这项高度跨学科的建议涉及小鼠基因组学、统计物理学、生物统计学、计算机科学、生物化学、流行病学和单细胞分析的全新组合，以了解基因组功能如何由环境塑造的基本问题。

 DESCRIPTION (provided by applicant): The environment is perhaps the major contributor to human disease, yet its effect is largely ignored in whole genome approaches to genetics. In this CEGS, we will attack head-on the mechanisms through which environment influences genomic function, focusing on two extremely important exposures highly relevant to human health: diet and its relationship to metabolic disease and cancer; and stress related to neuropsychiatric disease. This requires nearly complete control of the experimental system in a way that cannot be done in humans. Our first aim is develop a new foundational experimental mouse model for understanding gene-environment interaction (GxE). We will expose crosses of the genetically heterogeneous Collaborative Cross population of mice to three well-controlled diets - Western, Mediterranean, ketogenic - and measure phenotypes across organ systems representing metabolic and cardiovascular disease. We will also determine the effects of diet on azoxymethane-induced colon tumors; as well as stress on phenotypes relevant to neuropsychiatric disease. We will couple these analyses to whole genome bisulfite sequencing, chromatin accessibility analysis and transcriptomics of target tissues including liver, adipose tissue, colon, hippocampus, prefrontal cortex, and blood, measuring the nature and flow of information among environment, genome, epigenome, and transcriptome in determining phenotype. Our second aim is to develop new statistical methods as well as a novel mathematical framework for handling the interaction between genetics, epigenetics, and exposure, which will allow us to model how information is passed between these three domains to ultimately shape phenotype. These methods include causal inference testing, analysis of genomically discontiguous genotype-epigenotype relationships, and novel stochastic approaches based on fundamental concepts of statistical physics and information theory. Our third aim is to perform replication in naïve animals and in highly relevant human epidemiologic cohorts: DWH and ALSPAC for diet exposures and metabolic disorders; NHSII and EPIC for diet and colon cancer; and ALSPAC and PIRC for stress and behavioral traits. Our fourth aim is to develop and promulgate new measurement, analytical, and computational technologies for comprehensive genomic analysis of GxE. These include new biological resources and software packages, as well as biochemical, cellular and computational tools to test and improve the models and conclusions from the other Aims, and of broad general use to the genomics community, including: analysis of single or multiple marks for determining long-range GxE relationships; single cell and in situ analysis of gene expression and epigenetic modifications; and novel computational approaches including ultrafast alignment of large datasets. This highly interdisciplinary proposal involves completely novel combinations of mouse genomics, statistical physics, biostatistics, computer science, biochemistry, epidemiology, and single cell analysis, in order to understand the essential question of how genomic function is shaped by the environment.