Equipment Supplement: Genomic and Systemic Approaches of Evolutionary Mechanisms

设备补充：进化机制的基因组和系统方法

• 批准号: 10793042
• 负责人: JIANZHI ZHANG
• 金额: $ 4.24万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10793042
• 关键词: Aging; Area; Biological Models; Biology; Computer Simulation; Data Analyses; Dependence; Development; Disease; Environment; Equipment; Evolution; Genes; Genetic; Genetic Epistasis; Genetic study; Genome; Genomic approach; Genomics; Human; Individual; Joints; Light; Mammals; Maps; Molecular; Molecular Biology; Molecular Genetics; Mutation; Pattern; Phenotype; Prevalence; Process; RNA Editing; Research; Role; Technology; Testing; Theoretical model; Yeasts; biological systems; disease-causing mutation; driving force; environmental adaptation; fitness; functional genomics; gene interaction; genomic data; human disease; laboratory experiment; pleiotropism; programs

Project Summary The long-term objective of the PI's research program is to discover and understand general principles of evolution in terms of molecular genetic mechanisms and driving forces. This is a rapidly progressing area, thanks to the technological revolution in molecular biology and genomics, rapid accumulation of genome sequences and functional genomic data, and most importantly, conceptual developments in various fields of biology. Genomic and systemic approaches to evolution are especially valuable, because the genomic approach allows assessing the generalities and relative contributions of individual mechanisms discovered and the systemic approach helps refocus the study of evolutionary processes from roles of individual genes/mutations to those of interactions among genes/mutations (and the environment), which are key to uncovering the inner workings and evolution of biological systems. The PI's lab studies evolutionary mechanisms from genomic and systemic perspectives using multiple model systems (mostly yeast and mammals) and a combination of theoretical modeling, computer simulation, integrative data analysis, laboratory experimental evolution, and molecular and genomic experimentation. This proposal centers on two related themes that are of fundamental importance to evolution: epistasis and pleiotropy. On the topic of epistasis, the PI and his team will characterize patterns of intragenic and intergenic epistasis by mapping fitness landscapes of representative genes and joint fitness landscapes of pairs of interacting genes, study the genetic background dependency of gene essentiality at the genomic scale, experimentally test the hypothesis that the existence and persistence of RNA editing is explained by evolutionary entrenchment, and attempt to resolve the apparently contradictory inferences of epistasis patterns from adaptive evolution and mutation accumulation. On the topic of pleiotropy, the PI and his team will map multi-environment fitness landscapes of representative genes to study general patterns of environmental pleiotropy of mutations, identify common loci of environmental adaptations, quantify the influence of pleiotropy on molecular adaptations in changing environments, and assess the impact of pleiotropy on the rate of phenotypic evolution and human aging and disease. Together, these projects promise to deepen the understanding of the genetic mechanisms and driving forces of evolution and shed light on disease mechanisms and prevalence.

项目摘要 PI研究计划的长期目标是发现和理解 就分子遗传机制和驱动力而言。这是一个快速发展的领域， 得益于分子生物学和基因组学的技术革命，基因组的快速积累 序列和功能基因组数据，最重要的是，在各个领域的概念发展 生物学。基因组和全身进化方法特别有价值，因为基因组 方法允许评估发现的个体机制的一般性和相对贡献和 系统性方法有助于重新调整个人角色的进化过程 基因/突变基因/突变（以及环境）之间相互作用的基因/突变，这是对 揭示生物系统的内部起作用和演变。 PI的实验室研究进化 使用多种模型系统（主要是酵母， 哺乳动物）以及理论建模，计算机模拟，综合数据分析的组合， 实验室实验进化以及分子和基因组实验。该提议以两个为中心 对进化至关重要的相关主题：上毒和多效性。关于主题 epistasis，Pi和他的团队将通过映射来表征基因内和基因间的遗传学模式 代表基因的适应性景观和相互作用基因对的关节适应性景观，研究 基因本质在基因组量表上的遗传背景依赖性，实验检验假设 RNA编辑的存在和持久性是通过进化的根源来解释的，并试图尝试 从适应性进化和突变来解决上毒模式明显矛盾的推论 积累。关于多效性的话题，PI和他的团队将绘制多种环境健身景观 代表性基因研究突变环境多效性的一般模式，鉴定共同基因座 环境适应，量化多效性对分子适应的影响 环境，并评估多效性对表型进化和人类衰老率的影响 疾病。这些项目一起有望加深对遗传机制和驱动的理解 进化的力量并阐明了疾病机制和患病率。