A path to personalized phenotypic prediction: unlocking the context-dependency of allelic effects

个性化表型预测之路：解锁等位基因效应的背景依赖性

• 批准号: 10552203
• 负责人: Julien Ayroles
• 金额: $ 43.74万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-18 至 2027-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10552203
• 关键词: Accounting; Address; Alleles; Complex; Dependence; Disease; Drosophila genus; Environment; Genetic; Genetic Variation; Genome; Genomic Segment; Genomics; Genotype; Goals; Health; Human; Human Genetics; Individual; Life; Medicine; Modeling; Modernization; Molecular; Persons; Phenotype; Physiological; Play; Population; Process; Recording of previous events; Research; Role; Shapes; Societies; Technology; Testing; Time; Variant; Work; disorder risk; environmental change; environmental stressor; genetic makeup; innovation; interest; lens; precision medicine; pressure; programs; resilience; tool; trait

PROJECT SUMMARY Many of our most onerous health burdens today are driven by complex and poorly understood interactions between a person’s genetic makeup and his or her environment. In other words, genetic variation may predispose individuals toward physiological sensitivity or resilience in the face of environmental perturbations. Our modern environments are deeply diverged from the ancestral selective pressures that have shaped human genetic variation through evolutionary time, raising the question of how much the “mismatch” between our genomes and modern life is responsible for the non-communicable diseases that plague modern societies. This concept, known as the evolutionary mismatch hypothesis, has become a central tenet of evolutionary medicine and has potentially profound implications for how we study, manage, and treat a long list of conditions thought to arise from genomes mismatched to our modern environments. However, this hypothesis has been difficult to robustly test in practice, perhaps in part because we do not fully understand the mechanistic basis underlying this phenomenon. Under a mismatch model, we would expect genetic variation that was neutral or beneficial in past environments to become disease-causing in modern environments; in other words, we would expect this mismatch to generate “genotype-by-environment” (GxE) interactions, such that some genetic effects on health are environmentally dependent. My lab’s goal is to advance our understanding of how and why some individuals are more sensitive to environmental stressors than others, and to identify the molecular and genetic drivers of this variation. Work in my group has clearly established that the contribution of GxE to phenotypic variation is pervasive and it is generally underestimated. We now want to move beyond accounting for the variance explained by GxE and gain a mechanistic understanding of how these interactions shape phenotypic variation and drive disease risk. Over the next 5 years, a major theme of my lab will be to use evolutionary mismatch as a lens to study GxE. We aim to understand: (1) What makes a specific genomic region sensitive to its environmental context? (2) What role does population evolutionary history play in this process? (3) Why and how some individuals appear to be more sensitive than others to environmental perturbation? We are particularly interested in studying a class of genetic effects that are only revealed by environmental change (also known as “cryptic genetic variation”). Understanding the mechanistic underpinnings of how this class of variants drive phenotypic variation is one of the major goals of my research program. Technological advances have fueled the ascent of personal genomics and the promise of precision medicine. However, to unlock this potential, we must first understand how the environmental and genetic interactions unique to each individual contribute to variation in complex traits. This is the primary goal of this application and the focus of my research program – my work leverages these tools to address questions related to the context-dependency of allelic effects using a powerful, evolutionary lens. We conduct this work using both Drosophila and humans as a model.

项目摘要 我们今天许多最繁重的健康负担是由复杂和知之甚少的相互作用驱动的 一个人的基因组成和他或她的环境之间的关系。换句话说，遗传变异可能 使个体在面对环境干扰时倾向于生理敏感性或弹性。 我们的现代环境与祖先的选择压力有很大的不同， 通过进化时间的遗传变异，提出了一个问题，我们之间的“不匹配”有多少。 基因组和现代生活是困扰现代社会的非传染性疾病的根源。这 一个被称为进化失配假说的概念，已经成为进化医学的核心原则 并对我们如何研究、管理和治疗一长串被认为是 基因组与我们现代环境的不匹配。然而，这一假设很难解释。 在实践中进行强有力的测试，也许部分原因是我们没有完全理解潜在的机械基础， 这种现象。在错配模型下，我们预计遗传变异在遗传学中是中性的或有益的。 过去的环境在现代环境中成为致病因素;换句话说， 不匹配产生“基因型与环境”（GxE）相互作用，例如对健康的一些遗传影响 都依赖于环境。我的实验室的目标是加深我们对某些人 比其他人对环境压力更敏感，并确定分子和遗传驱动因素， 这种变化。我的小组的工作已经清楚地确定，GxE对表型变异的贡献是 普遍被低估了。我们现在要做的不仅仅是考虑 GxE解释，并获得这些相互作用如何形成表型变异的机制理解 and drive驱动disease疾病risk风险.在接下来的5年里，我实验室的一个主要主题将是使用进化失配作为 一个研究GxE的透镜。我们的目标是了解：（1）是什么使一个特定的基因组区域对其敏感？ 环境背景？(2)种群进化史在这一过程中扮演了什么样的角色？(3)为什么和如何 有些人似乎比其他人更敏感的环境扰动？我们特别 有兴趣研究一类遗传效应，只有揭示了环境变化（也被称为 “隐性遗传变异”）。了解这类变体如何驱动的机械基础 表型变异是我研究计划的主要目标之一。技术进步推动了 个人基因组学的兴起和精准医疗的前景。然而，为了释放这种潜力，我们必须 首先了解每个个体独特的环境和遗传相互作用如何促成变异 复杂的特征。这是本应用程序的主要目标，也是我研究计划的重点-我的工作 利用这些工具来解决与等位基因效应的上下文依赖性相关的问题， 进化的透镜。我们使用果蝇和人类作为模型进行这项工作。