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.

项目摘要 理解适应的一般规则对于治疗由进化引起的疾病具有重要意义。 实体，如癌症和耐药感染。为了揭示这些一般规律，以前的 研究揭示了一个看似矛盾的现象。一方面，在选择性压力下， 适应性突变出现迅速，具有较大的适应性效应，定位于少数功能相似的基因， 可能会采用相同的适应策略。另一方面，实验室进化的生物体显示出广泛的 不同的生理变化。这意味着定向选择增加而不是减少 表型多样性这一现象可能解释了我们有限的能力来预测的有效性， 抗癌疗法，因为即使是基因相似的癌症也可能具有高度不同的生理学。在这 项目中，我将使用一个收集了几百个经过充分研究的自适应S。酿酒酵母突变体，分离自 单一的进化实验，以测试选择如何产生多样性的两个机制假设。我 工作假设是，选择通过塑性反应的组合损失产生多样性。的 另一种假设是，选择通过获得新的反应产生多样性。 为了区分这两种假设，我将测量适应性细胞的分子表型。 两种RNA测序技术。在目标1中，我将小心地对10使用批量RNA测序 选择的突变体，在他们进化的环境中生长，为了获得第一个洞察力， 适应策略的分子机制。在目标2中，我将使用最先进的高通量， 条形码感知RNA测序方法称为Split-Seq，以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 在进化环境中实现高适应性，在其他环境中通过丧失 可塑性或创造新的反应。揭示选择如何产生多样性的机制， 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，我接受了分子遗传学的强有力的培训，并学习了基本的湿实验室技能， 很少接触进化论或基因组学。承担这个项目将大大扩展我的概念 和技术工具包，因为我将学习分子进化和人口遗传学，以及基因组学 比如条形码追踪和RNA测序。我将接受正式和非正式的培训， 理论，编程，基因组学数据分析，赠款写作和专业领导。这会让我做好准备 成为分子和进化的跨学科领域的独立研究者和领导者 生物学