Genetics of adaptation to toxic environments

适应有毒环境的遗传学

• 批准号: 10283620
• 负责人: Marianthi Karageorgi
• 金额: $ 10万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-09 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10283620
• 关键词: Adopted; Agreement; Alleles; Aloral; Animals; Antibiotics; Award; Biological Models; Biology; Butterflies; CRISPR/Cas technology; Cardiac Glycosides; Chromosome Mapping; Defect; Drosophila genus; Drosophila melanogaster; Environment; Evolution; Genetic; Genetic Engineering; Genetic Polymorphism; Genetic study; Genome; Genome engineering; Genomic approach; Genomics; Genotype; Goals; Insecta; Knowledge; Laboratories; Laboratory Research; Learning; Linkage Disequilibrium; Maps; Mentors; Mutation; Na(+)-K(+)-Exchanging ATPase; Neurologic; Neurons; Pesticides; Phase; Plants; Play; Population; Process; Proteins; Recording of previous events; Research; Resistance; Resolution; Role; Seizures; Specialist; System; Technology; Testing; Time; Toxin; Training; Work; anthropogenesis; base; career; cost; fitness; genome sequencing; genome-wide; in vivo; resistance mutation; theories; tool; whole genome

SUMMARY Resistance to toxins often evolves via major effect mutations in the target protein. Theory predicts that these major effect mutations carry fitness costs, which are subsequently resolved or ameliorated via compensatory mutations. Yet, characterization of compensatory mutations has remained elusive because their testing has been hampered by a lack of tools. With the advent of genome sequencing and genome engineering, we can now identify candidate compensatory mutations and rigorously test them in vivo. Here, I propose to use Drosophila subobscura as a new model system to fully characterize compensatory mutations ameliorating neuronal costs of toxin resistance mutations in ATPα (α-subunit of the Na+, K+-ATPase). I will adopt both a candidate-based and an unbiased genome-wide approach to characterize compensatory mutations, which should allow me gain a complete view of compensatory evolution in Drosophila subobscura. During the K99 phase (first and second aims), I will adopt the candidate-based approach to explore compensatory mutations within the resistant ATPα alleles of D. subobscura. Under the first aim, I will employ a population genomic approach to identify candidate compensatory mutations within the resistant ATPα alleles. Under the second aim, I will employ a genome engineering approach to characterize the candidate compensatory mutations from the first aim by editing them together with the resistance mutations in the sensitive ATPα allele of D. melanogaster. During the R00 phase (third and fourth aims), I will adopt the unbiased genome-wide approach to explore compensatory mutations outside the resistant ATPα alleles of D. subobscura (“modifier locus”). Under the third aim, I will employ a genome engineering approach to introduce the resistant ATPα alleles of D. subobscura in a sensitive D. subobscura background to first validate the presence of a “modifier locus”. Under the fourth aim, I will use gene mapping to characterize the modifier locus. The collective results of this project will provide a detailed picture where in the genome compensatory mutations evolve and in which order they evolve relative to the the resistance mutations. A K99 Award would allow me to receive training in population genomics and sequencing technologies and provide time to extend my expertise in genome engineering and theory on the genetics of adaptation to toxic environments. The training phase of this proposal will be performed in the laboratory of Dr. Dmitri Petrov, which is ideal for exchanging exciting idea and learning population genomics as he is a leader in the Drosophila population genomics of adaptation. Stanford and the the Department of Biology provide an excellent environment and facilities for the proposed work. My long term career goal is to establish my independent academic research laboratory where I will study the genetics of adaptation to toxic environments.

总结 对毒素的抗性通常通过靶蛋白中的主要效应突变而进化。理论预测，这些 主要效应突变带来适应性成本，随后通过补偿性突变解决或改善适应性成本。 突变。然而，补偿突变的特征仍然难以捉摸，因为它们的测试已经 由于缺乏工具而受到阻碍。随着基因组测序和基因组工程的出现，我们可以 现在确定候选的补偿突变，并在体内进行严格的测试。在这里，我建议使用 果蝇subobscura作为一个新的模式系统，以充分表征补偿突变改善 ATPα（Na+，K+-ATP酶的α-亚基）毒素抗性突变的神经元代价。我将采取两个A 基于候选人和无偏见的全基因组方法来表征补偿突变， 应该可以让我对果蝇的补偿进化有一个完整的了解。在K99 第一阶段（第一和第二目标），我将采用基于候选人的方法来探索补偿突变 在D. subobscura。在第一个目标下，我将使用一个人口基因组， 鉴定耐药ATPα等位基因内候选补偿突变的方法。根据第二个 目的，我将采用基因组工程的方法来表征候选的补偿突变， 第一个目标是将它们与D. 黑腹菌在R 00阶段（第三和第四个目标），我将采用无偏的全基因组方法 探讨D. subobscura（“修饰基因座”）。 第三个目标是利用基因组工程的方法，将D. 敏感D. subobscura背景，以首先验证“修饰基因座”的存在。下 第四个目标是利用基因定位技术对修饰基因进行定位。这个项目的集体成果 将提供一个详细的图片，在基因组中的补偿突变进化，以及以何种顺序， 相对于耐药突变的进化。 K99奖将使我能够接受人口基因组学和测序技术方面的培训， 提供时间来扩展我在基因组工程和适应有毒物质遗传学理论方面的专业知识， 环境.本提案的培训阶段将在Dmitri Petrov博士的实验室进行， 这是理想的交流令人兴奋的想法和学习人口基因组学，因为他是一个领导者， 果蝇种群适应性基因组学。斯坦福大学和生物系提供了一个 良好的工作环境和设施。我的长期职业目标是建立我的 我将在这里研究适应有毒环境的遗传学。