Understanding the mechanism of diversity generation through directional selection

通过定向选择理解多样性产生的机制

• 批准号: 10749798
• 负责人: Alexandra Khristich
• 金额: $ 7.18万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-14 至 2025-08-13
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10749798
• 关键词: Adaptive Behaviors; Antifungal Agents; Awareness; Bar Codes; Behavior; Biological Assay; Biology; Cells; Classification; Collection; Communities; Cyclic AMP-Dependent Protein Kinases; DNA; Data; Data Analyses; Data Set; Development; Disease; Doctor of Philosophy; Drug resistance; Effectiveness; Environment; Evolution; Exhibits; Exposure to; Gene Expression; Generations; Genes; Genetic; Genome; Genomics; Genotype; Glucose; Goals; Grant; Growth; Home environment; Individual; Infection; Laboratories; Leadership; Learning; Malignant Neoplasms; Measurement; Measures; Methods; Molecular; Molecular Evolution; Molecular Genetics; Mutation; Nutrient Depletion; Organism; Osmolar Concentration; Pathway interactions; Pattern; Phase; Phenotype; Physiological; Physiology; Population Genetics; Process; Recurrence; Research; Research Personnel; Resistance; Resources; Saccharomyces cerevisiae; Signal Pathway; Split-Pool Ligation Transcriptome sequencing; Technology; Testing; Therapeutic; Time; Training; Writing; Yeasts; cancer therapy; combinatorial; drug resistant pathogen; expectation; experimental study; fitness; genomic data; insight; loss of function mutation; model organism; molecular phenotype; mutant; novel; pathogen; pressure; response; single-cell RNA sequencing; skills; theories; therapy development; transcriptome; transcriptome sequencing; transcriptomics

PROJECT SUMMARY Understanding the general rules of adaptation has implications for treating diseases caused by evolving entities such as cancer and drug-resistant infections. In attempts to uncover these general rules, previous research has revealed a seemingly paradoxical phenomenon. On the one hand, under selective pressure, adaptive mutations arise quickly, have large fitness effects, localize to a few functionally similar genes, and likely exploit the same adaptive strategy. On the other hand, laboratory-evolved organisms show a wide range of diverse physiological changes. This means that directional selection increases rather than decreases phenotypic diversity. This phenomenon likely explains our limited ability to predict the effectiveness of anticancer therapies, because even genetically similar cancers can have highly diverse physiologies. In this project, I will use a collection of several hundred well-studied adaptive S. cerevisiae mutants, isolated from a single evolution experiment, to test two mechanistic hypotheses of how selection might generate diversity. My working hypothesis is that selection generates diversity through combinatorial loss of plastic responses. The alternative hypothesis is that selection generates diversity through the gain of novel responses. To distinguish between these two hypotheses, I will measure the molecular phenotypes of the adaptive mutants with two RNA sequencing technologies. In Aim 1, I will use bulk RNA sequencing on 10 carefully selected mutants, grown in the environment in which they evolved, in order to gain the first insight into the molecular mechanism of their adaptive strategy. In Aim 2, I will use a state-of-the-art, high-throughput, barcode-aware RNA sequencing approach called Split-Seq to measure the full scope of the adaptive mutants' phenotypes which are most prominent in various extreme environments. This will reveal if the adaptive mutants achieve high fitness in the evolution environment and high diversity in other environments through loss of plasticity or by creating novel responses. Uncovering the mechanism of how selection generates diversity will contribute to our general understanding of adaptation and have implications for treating diseases driven by evolutionary adaptation, such as cancer and drug-resistant infections. During my PhD, I received strong training in molecular genetics and learned basic wet lab skills but had little exposure to evolutionary theory or genomics. Undertaking this project will greatly expand my conceptual and technological toolkit, as I will learn molecular evolution and population genetics, as well as genomics methods like barcode tracking and RNA sequencing. I will receive formal and informal training in evolutionary theory, programming, genomics data analysis, grant writing, and professional leadership. This will prepare me to become an independent researcher and leader in the interdisciplinary field of molecular and evolutionary biology.

项目总结 了解适应的一般规律对于治疗由进化引起的疾病具有重要意义 癌症和耐药感染等实体。在试图揭示这些一般规则时，以前的 研究揭示了一个看似自相矛盾的现象。一方面，在选择性的压力下， 适应性突变迅速出现，具有很大的适应效应，定位于几个功能相似的基因，以及 很可能会利用同样的适应性策略。另一方面，实验室进化的生物体表现出广泛的 不同的生理变化。这意味着方向选择增加而不是减少 表型多样性。这一现象很可能解释了我们有限的预测能力 抗癌疗法，因为即使是基因相似的癌症也可能有非常不同的生理特征。在这 项目中，我将使用数百个经过充分研究的酿酒酵母适应性突变体的集合，这些突变体是从 单一进化实验，以检验关于选择如何产生多样性的两个机械性假设。我的 工作假说是，选择通过塑料反应的组合损失来产生多样性。这个 另一种假设是，选择通过获得新奇的反应来产生多样性。 为了区分这两个假设，我将测量适应性 使用两种RNA测序技术的突变体。在目标1中，我将仔细使用10条上的批量RNA测序 选定的突变体，生长在它们进化的环境中，以便第一次洞察 它们适应策略的分子机制。在目标2中，我将使用最先进的、高吞吐量、 条形码感知的RNA测序方法Split-Seq用于测量适应性突变体的全部范围 在各种极端环境中最突出的表型。这将揭示适应性突变体是否 在进化环境中实现高适应性，在其他环境中通过丢失 可塑性或通过创造新的反应。揭示选择如何产生多样性的机制将 有助于我们对适应的一般理解，并对治疗由 进化适应，如癌症和耐药感染。 在我的博士学位期间，我接受了强大的分子遗传学培训，并学习了基本的湿法实验室技能，但 很少接触进化论或基因组学。承担这个项目将极大地扩展我的概念 和技术工具包，因为我将学习分子进化和种群遗传学，以及基因组学 条形码跟踪和RNA测序等方法。我将接受正式和非正式的进化论培训 理论、编程、基因组数据分析、拨款撰写和专业领导力。这会让我做好准备 成为分子和进化交叉学科领域的独立研究人员和领导者 生物学。