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 ‘遗传上的菌株（COV）是一个重要的进化机制 用于生成遗传变异，但它也是主机切换的重要驱动力。 被认为是起源于动物（尤其是蝙蝠）和HABE的进化证据 历史。 不清楚。 将检验以下假设：两个COV之间重组的可能性是遗传距离的一个函数， 并且这种概率通过生态或进化效应进一步改变。 随着亲本菌株之间的遗传距离的增加而招募 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实际上将同时选择或进化选择压力。 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。 这将测试重组项目何时依靠父母之间的遗传距离，并将 还显示重组是在AIM 2中随机发生的基因组还是“热点”。 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。 距离），加上任何生态或进化修饰符（例如，自然选择）。 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，使我们能够消除遗传和生态因素的贡献 对于这两个病毒将重新组合的可能性。 在COV重组的潜力和概率中，我们将推断这些效果以产生 一个空间模型，估计世界各地的COV风险（AIM 3） 整合我们独特的全球COV监视数据 将产生一个预测最有可能重组世界的世界的风险图。