Effects of genetic background on adaptive evolution

遗传背景对适应性进化的影响

基本信息

批准号：
10397123
负责人：
Peter Andolfatto
金额：
$ 32.96万
依托单位：
COLUMBIA UNIV NEW YORK MORNINGSIDE
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10397123
关键词：
ATP phosphohydrolase Address Amino Acid Substitution Amino Acids Animal Model Animals Behavior Biology CRISPR/Cas technology Cardiac Glycosides Cre lox recombination system Data Dependence Development Disease Drosophila genus Drosophila melanogaster Proteins Drug Targeting Engineering Evolution Exhibits Fertility Gene Expression Profiling Genes Genetic Genetic Determinism Genetic Engineering Genetic Epistasis Genetic Variation Genome Genome engineering Genomics Homeostasis Human Human Biology In Vitro Individual Insecta Learning Link Maps Modeling Molecular Molecular Genetics Mutation Na(+)-K(+)-Exchanging ATPase Natural Selections Nature Neurologic Organism Outcome Phenotype Physiological Plants Population Population Genetics Process Property Proteins Quantitative Trait Loci Recurrence Resistance Role Shapes Site Steroids System Technology Time Toxic effect Toxin Variant Vertebrates Work comparative genomics experience fitness genetic analysis genetic architecture genetic predictors genome editing genome wide association study human disease in vivo inhibitor innovation insight novel pathogenic bacteria pathogenic virus protein function steroid dependence steroid glycoside tool trait whole genome

项目摘要

Project Summary To what extent is adaptive evolution predictable? Despite its importance in understanding the biology of human diseases, including the evolution of viral and bacterial pathogens, the dynamics of genetic adaptation are still poorly understood. In particular, few examples yet exist that have been dissected to the molecular level. Examples of adaptations from natural systems and the use of model organisms are powerful tools that can be combined to make progress on this difficult question. We have employed instances of “parallel evolution”, involving assemblages of species experiencing a common regime of natural selection, to evaluate multiple outcomes of the process of adaptation. With this information, we can learn about recurrent features of adaptation and infer constraints and regularities in the adaptive process. Our work focused on the biomedically-important interaction between Na+,K+-ATPases and their regulatory steroidal-glycosides that a large variety of plants and animals use as toxins to defend themselves from being eaten. Using a diverse set of animals that have independently evolved resistance to steroidal-glycoside toxicity, including insects and vertebrates, we discovered these diverse species most often evolve resistance via a small number of possible options (i.e. involving only three of 41 possible sites in the protein that could be modified to confer resistance). These findings suggest that adaptive evolution is often path-dependent, implying that the individual components of an adaptation must evolve in a prescribed, and ultimately predictable, order. They also raise numerous questions about the nature of this path dependency, including the extent to which it emerges from interactions among residues within a protein, or from the genomic background of the species; whether it similarly constrains adaptation over short and longer time scales, and how generally it applies in adaptive protein evolution. Here we propose three aims that address these questions, by combining approaches from evolutionary genomics and molecular genetics. In Aim 1, we will use genome engineering in Drosophila to elucidate the path dependence of the steroidal-glycoside resistance adaptation both at the level of its primary target (Na+,K+-ATPase) and at the level of the whole genome. In Aim 2, we will determine which and how many genomic factors contribute to naturally occurring variation within Drosophila populations. This information will reveal the relationship between within- population and between-species genetic variation underlying the same trait, connecting short- and long-term dynamics of the adaptive process. In Aim 3, we will use principles learned from molecular adaptation at Na+,K+-ATPase to computationally predict and use genome engineering to functionally validate path dependent adaptation dynamics in Drosophila for a diverse group of proteins, many of which (like Na+,K+-ATPase) have important roles in neurological development and homeostasis. Together this work will greatly increase our understanding of the constraints on adaptive protein evolution and the predictability of the genetic changes by which novel phenotypes emerge.

项目摘要尽管它在理解人类疾病的生物学方面，自适应进化在多大程度上可以预测？涵盖病毒和双性病原体的演变，仍然了解了遗传适应性的动力学。特别是，很少有例子被剖析到分子水平。系统和模型生物的美国是强大的工具，可以合并以在Difficalt上取得进展问题。我们采用了“平行进化”的实例 WITH TIS INFORMATION, WITH TITHOSSSSSSSSSSSSSSSSS OF someet some OUTCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES OFCOMES some 了解适应性的经常性特征，并在适应过程中推断约束和规律性专注于Na+，K+-Atpass和常规糖苷之间的生物医学重要相互作用各种各样的植物和动物都用毒素来捍卫自己免于被食用。独立发展对甲固醇 - 糖苷毒性的抗性，包括昆虫和脊椎动物，我们发现了多种物种通常通过少量可能的选择而发展的抗性蛋白质中的41个可能的位点中有3个蛋白质蛋白质以赋予抗性）。进化通常是道路向前的，这意味着适应的个体组成部分被铭刻，预先列出，最终可以预测，他们也提出了许多追求。它从蛋白质内居民之间的国际相互作用或从您的基因组背景中产生的程度物种;它是否类似地限制了适应性的短时尺度，以及自适应蛋白的进化。进化基因组学和分子遗传学。类固醇 - 糖苷耐药性的路径依赖性在IS主要靶标（Na+，K+-ATPase）的水平上均在AIM 2中的整个基因组水平上，我们将确定整个基因组以及多少基因组因素。果蝇种群中自然发生的变化。种群和种类之间的遗传变异具有相同的特征，连接了短期和长期动态 AIM 3中的自适应过程，我们将使用Na+，K+ATPase的分子自适应原理计算预测和使用基因组工程来在功能上验证路径下的适应动力学果蝇论蛋白质群，其中许多（例如Na+，K+-ATPase）在神经学中具有重要作用发展和体内稳态。蛋白质进化和遗传变化的可预测性出现。