Genetic and ecological determinants of coronavirus recombination

冠状病毒重组的遗传和生态决定因素

• 批准号: 10271111
• 负责人: Simon J Anthony
• 金额: $ 37.95万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-17 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10271111
• 关键词: Animals; Automobile Driving; Cell Line; Chiroptera; Coronavirus; Country; Data; Databases; Daughter; Detection; Event; Frequencies; Genbank; Genes; Genetic; Genetic Materials; Genetic Recombination; Genetic Variation; Genome; Genomics; Goals; Hot Spot; Human; Laboratories; Laboratory Study; Location; Logistic Models; Maps; Methods; Modeling; Natural Selections; Nature; Observational Study; Parents; Pattern; Phylogenetic Analysis; Probability; Process; Proteins; Public Health; Recombinants; Recording of previous events; Reporting; Risk; Risk Estimate; Role; Series; Site; Spatial Distribution; Statistical Models; Structure; Surveys; Testing; Virus; Work; base; comparative genomics; cross-species transmission; experimental study; human coronavirus; improved; laboratory experiment; mathematical model; nanopore; novel coronavirus; pressure; programs; single molecule; surveillance data; tissue tropism; trend

PROJECT SUMMARY: Recombination is the process by which two viruses exchange part of their genetic material to produce a ‘daughter’ strain that is genetically distinct. For coronaviruses (CoVs), it is an important evolutionary mechanism for generating genetic variation, but it is also an important driver of host switching. Most CoVs in humans are thought to have originated in animals (in particular, bats) and have evidence of recombination in their evolutionary history. Despite the relevance to public health, the mechanism, drivers, and limitations to recombination remain unclear. Using a combination of laboratory experiments, comparative genomics, and mathematical modeling, we will test the hypothesis that the probability of recombination between two CoVs is a function of genetic distance, and that this probability is further modified by ecological or evolutionary effects. In other words, the likelihood of recombination decreases as the genetic distance between the parental strains increases (presumably because of genetic or structural incompatibilities), but is also impacted by ecological processes such as the chance that two CoVs will actually co-occur or evolutionary selection pressure. We will test three aims: In Aim 1, we will employ laboratory studies and co-infect human and bat cell lines with pairs of CoVs over a phylogenetic gradient. This will test whether the probability of recombination is related to genetic distance between the parents, and will also show whether recombination occurs randomly throughout the genome or in particular ‘hot-spots’. In Aim 2, we will evaluate naturally occurring CoVs using genomes available in public databases or from our own previous work. Presumably, naturally occurring recombinants will be the result of any genetic limitations (e.g., genetic distance), plus any ecological or evolutionary modifiers (e.g., natural selection). Thus, by comparing the laboratory (Aim 1) and observational (Aim 2) studies, we can begin to identify patterns that would remain unclear with experimental data alone, allowing us to disentangle the contributions of both genetic and ecological factors to the probability that any two viruses will recombine. This understanding can then be used to improve predictions of both the potential and probability of CoV recombination. Finally, we will extrapolate these effects to generate a spatial model that estimates of the risk of recombinant CoVs arising in different parts of the world (Aim 3). By integrating our unique global CoV surveillance data (>31,000 animals from >25 countries surveyed for CoVs) we will produce a risk map predicting regions of the world where recombination is most likely.

项目摘要： 重组是两种病毒交换其遗传物质以产生A的过程 遗传上不同的“女儿”菌株。对于冠状病毒（COVS），它是重要的进化机制 用于生成遗传变异，但它也是主机切换的重要驱动力。人类中的大多数COV是 被认为是起源于动物（尤其是蝙蝠）的，并具有重组的证据 历史。尽管与公共卫生有关 不清楚。利用实验室实验，比较基因组学和数学建模的组合，我们 将检验以下假设：两个COV之间重组的可能性是遗传距离的函数， 并且这种概率通过生态或进化效应进一步改变。换句话说， 随着父母菌株之间的遗传距离的增加，重组的下降（以前是因为 遗传或结构性不兼容），但也受到生态过程的影响，例如 两个COV实际上将共发生或进化选择压力。我们将测试三个目标：在AIM 1中，我们将 在系统发育梯度上使用实验室研究并与成对的COV共同感染人和蝙蝠细胞系。 这将测试重组的可能性是否与父母之间的遗传距离有关，并将 还显示重组是否在整个基因组中随机发生，或者是“热点”。在AIM 2中， 我们将使用公共数据库中可用的基因组或以前的以前的基因组来评估自然发生的COV 工作。据推测，天然存在的重组将是任何遗传局限性的结果（例如遗传 距离），加上任何生态或进化修饰符（例如自然选择）。通过比较 实验室（AIM 1）和观察性研究（AIM 2）研究，我们可以开始确定尚不清楚的模式 仅使用实验数据，使我们能够解散遗传因素和生态因素的贡献 任何两种病毒都会重组的概率。然后可以使用这种理解来改善预测 COV重组的潜力和概率。最后，我们将推断这些效果以产生 一种空间模型，估计世界各地重组COV的风险（AIM 3）。经过 整合我们独特的全球COV监视数据（>来自25个对COV的国家 /地区的31,000只动物）我们 将产生一个预测最有可能重组世界的世界的风险图。