NSFDEB-BSF: Collaborative Research: RUI: The fitness cost of every single mutation in the HIV genome

这个合作项目涉及两名职业生涯早期的女性研究人员，一名来自美国，另一名来自以色列。他们的目标是使用新的实验室技术和新的统计方法来确定人类免疫缺陷病毒(HIV)基因组所有可能突变的适宜成本。突变是基因变异的最终来源，也是进化的燃料。但一个特定的突变是否会持续存在并导致种群内的变异，取决于它的适应成本。与那些健康成本很低或没有健康成本的突变相比，高健康成本的突变很可能会从人群中消除。突变适合度知识是进化生物学中许多基本问题的核心，但也具有关键的实际应用，例如，在预测抗生素、抗病毒药物和杀虫剂的耐药性进化方面。尽管这很重要，估计适应成本仍然是现代进化基因组学的关键挑战之一。研究人员将使用创新的基因组和计算方法分析75名艾滋病毒B亚型和C亚型患者的临床样本。由此产生的数据最终将使他们能够推断艾滋病毒基因组中每个单点突变的适应成本。该项目包括为STEM领域中代表性不足群体的本科生提供密集的指导和研究机会。这些学生还将获得国际经验。将开发一门新的研究生水平课程，内容是向公众传播科学。公众宣传将通过视频、公开讲座和访问当地学校进行。HIV是研究体内健康成本的理想模型系统：遗传多样性在每个宿主中迅速积累，来自不同患者的样本可以被视为独立的复制群体。然后，可以通过使用突变-选择平衡理论和平均患者的突变频率来推断健康成本。研究人员有三个主要目标。1)开发从突变频率推断适应度成本的统计方法。2)为低生物量样本开发高精度的下一代测序方法，并使用这些方法对患者样本中的HIV进行测序并推断突变频率。3)推断全球最流行的两个HIV-1亚型B和C亚型的健康成本高分辨率地图，并量化与背景相关的健康影响。实现这些目标将导致首次在体内完全分配基因组的适合性成本。这些创新方法的开发也将推广到任何存在独立种群的下一代测序(NGS)数据的系统。该奖项由国际科学与工程办公室共同资助。

This collaborative project involves two early career female researchers, one from the U.S. and the other from Israel. Their goal is to determine the fitness cost of all possible mutations in the human immunodeficiency virus (HIV) genome using new laboratory techniques and new statistical methods. Mutations are the ultimate source of genetic variation and the fuel of evolution. But whether a particular mutation persists and contributes to variation within a population is determined by its fitness cost. Mutations with high fitness costs will likely be eliminated from the population versus those with little or no fitness costs. Knowledge of mutational fitness is central to many basic questions in evolutionary biology, but also has critical practical application, for example, for predicting evolution of resistance to antibiotics, antiviral drugs, and pesticides. Despite this importance, estimating fitness costs remains one of the key challenges in modern evolutionary genomics. The researchers will analyze clinical samples from a combination of 75 HIV subtype B and subtype C patients using innovative genomic and computational methods. Resulting data will ultimately allow them to infer the fitness cost of every single point mutation in the HIV genome. The project includes intensive mentoring and research opportunities for undergraduate students from underrepresented groups in STEM fields. These students will also gain international experiences. A new graduate level course on communicating science to the public will be developed. Public outreach will occur via videos, public lectures, and visits to local schools. HIV is an ideal model system for studying in vivo fitness costs: Genetic diversity accumulates quickly in every host, and samples from different patients can be treated as independent replicate populations. Fitness costs can then be inferred by using the theory of mutation-selection balance and averaging mutation frequencies across patients. The researchers have three primary objectives. 1) Develop statistical methods for inferring fitness costs from mutation frequencies. 2) Develop highly accurate next generation sequencing approaches for low biomass samples, and use these to sequence HIV from patient samples and infer mutation frequencies. 3) Infer high-resolution maps of fitness costs in HIV-1 subtypes B and C, the two most prevalent subtypes across the globe, and quantify context-dependent fitness effects. Accomplishing these objectives will lead to the first complete in vivo distribution of fitness costs for a genome. Development of these innovative methods will also be generalizable to any system for which next generation sequencing (NGS) data exist for independent populations. This award is co-funded by the Office of International Science and Engineering.