Genome evolution across complex trait hierarchies

跨复杂性状层次的基因组进化

• 批准号: 10623062
• 负责人: Elizabeth Griep King
• 金额: $ 40.4万
• 依托单位: UNIVERSITY OF MISSOURI-COLUMBIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10623062
• 关键词: Address; Affect; Behavior; Biological Models; Caring; Communities; Complex; Coronary Arteriosclerosis; Drosophila genus; Energy Metabolism; Environment; Environmental Risk Factor; Evolution; Genetic; Genome; Genomics; Genotype; Health; Human; Individual; Knowledge; Longevity; Maps; Medical; Metabolic syndrome; Phenotype; Physiology; Population; Property; Research; causal variant; endurance exercise; fly; genetic variant; individual patient; innovation; insight; pleiotropism; precision medicine; trait

Project Summary Most human health traits are highly complex and hierarchical, in which a high-level trait (e.g., energy expenditure) is the product of the combined effects of a suite of sub-phenotypes. These trait hierarchies are typically influenced by many genetic variants of small effect that interact with one another and with environmental factors, making the identification of the causative variants a significant challenge. As a result, past research strategies have largely failed to fully address the complexity of most complex traits, leaving a significant knowledge gap in our understanding of the genetic basis of these traits. This project will use an innovative combination of a large multiparent mapping population and experimental evolution using the powerful fruit fly model system to identify the common mechanistic connections between complex traits and observe how these connections influence multitrait evolution. First, this project will simultaneously evolve flies targeting multiple trait hierarchies and track the genomic and phenotypic changes that occur during adaptation. Second, this project will leverage a large multiparent mapping population that has been used broadly in the genetics community to address fundamental questions about the generality of emergent properties of the genome, such as the extent of pleiotropy, genotype by environment interactions, and genetic background effects. Overall, this research will provide generalizable lessons about how genomes are connected to physiology to produce the interconnected set of traits that affect health across the lifespan.

项目摘要 大多数人类健康特征都是高度复杂和分层的，其中一个高级特征（例如，能量消耗） 是一系列亚表型综合作用的产物。这些特质层次结构通常是 受许多相互作用和与环境因素相互作用的小作用遗传变异的影响， 使得致病性变体的鉴定成为一个重大挑战。因此，过去的研究策略 在很大程度上未能完全解决大多数复杂特征的复杂性，在 我们对这些特征的遗传基础的理解。该项目将使用一个大型的创新组合 多亲作图群体和实验进化使用功能强大的果蝇模型系统来识别 复杂特征之间的常见机械联系，并观察这些联系如何影响 多性状进化首先，该项目将同时进化针对多个特征层次的苍蝇， 在适应过程中发生的基因组和表型变化。其次，该项目将利用大量 多亲作图群体，已被广泛用于遗传学界，以解决基本的 关于基因组涌现特性的一般性问题，如多效性的程度，基因型 环境相互作用和遗传背景效应。总的来说，这项研究将提供可推广的 关于基因组如何与生理学联系起来，产生一系列相互关联的特征， 整个生命周期的健康。