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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

基本信息

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
项目类别：
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

项目摘要

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.

项目总结