RAPID: finding virulence genes as therapeutic targets in Covid-19

这一快速奖励是由生物基础设施部(DBI)利用冠状病毒援助、救济和经济安全(CARE)法案的资金做出的。这项授予佐治亚大学的奖项将利用生物信息学工具来识别帮助SARS-COV-2跨越物种边界的毒力基因。识别人类SARS-COV-2及其近亲在蝙蝠、穿山甲和民间哺乳动物体内的共同基因变化，对于理解病毒的作用模式是重要的。确定哪些变化对SARS-COV-2的人类毒力有贡献尤其关键。研究人员将分析SARS-COV-2病毒的3,200+基因组和动物水库的冠状病毒基因组，以查看与毒力和新冠肺炎症状相关的基因变化。为了完成这项工作，将开发新的软件工具，以更好地利用现代计算机图形处理单元(GPU)进行高速并行计算。该项目将吸引研究生和REU参与者参与具有关键国家重要性的跨学科研究，并为未来的生物信息学研究提供有用的工具。该项目的目标是识别毒力基因，使SARS-COV-2能够跨越脊椎动物宿主的物种边界。该项目有三个主要部分：(1)通过合并方法在冠状病毒物种树内建立基因树；(2)在天然水库和人类SARS-COV-2之间的选择性扫描下测试共享的多态；(3)通过比较选择性扫描(毒力选择下)和不完全谱系排序的基因谱系来独立验证任务(2)中确定的候选。一个来自遗传学、生物信息学和传染病的跨学科团队将使用为图形处理器开发的一种新的最佳合并方法，在包含3200多个已发表的SARS-COV-2基因组的物种树中开发基因树。这些研究的结果将迅速传播并在同行评议的期刊上发表，在科学会议上提交，并通过共享软件库提供。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This RAPID award is made by the Division of Biological Infrastructure (DBI) using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act. This award to the University of Georgia will leverage bioinformatics tools to identify virulence genes that assisted SARS-COV-2 in jumping species boundaries. Identifying shared genetic changes between human SARS-COV-2 and its relatives in mammalian reservoirs in the bat, pangolin, and civit is important to understanding the virus mode of action. It is especially critical to identify which of the changes contribute to human virulence of SARS-COV-2. The researchers will analyze 3200+ genomes from SARS-COV-2 and coronavirus genomes from animal reservoirs to look at genetic changes associated with virulence and COVID-19 symptoms. To accomplish this work, new software tools will be developed to better leverage modern computer graphics processing units (GPUs) for high-speed parallel computing. The project will engage graduate students and REU participants in interdisciplinary research of critical national importance and contribute useful tools for future bioinformatic research.The objective of this project is to identify virulence genes that enable SARS-COV-2 to jump species boundaries from vertebrate reservoirs. The project has three main components: (1) building gene trees within species trees of coronavirus by coalescent methods; (2) testing for shared polymorphisms under selective sweep between natural reservoirs and human SARS-COV-2; (3) validating candidates identified in task (2) independently by comparing gene genealogies for selective sweep (under selection for virulence) vs. incomplete lineage sorting. An interdisciplinary team from genetics, bioinformatics, and infectious diseases will develop gene trees within a species tree of 3,200+ published SARS-COV-2 genomes using a novel BEST coalescent method developed for GPUs. Results from these studies will be rapidly disseminated and published in peer-reviewed journals, presented at scientific conferences, and made available through shared software repositories.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.