RAPID: Accelerating Phylodynamic Analyses of SARS-CoV-2

利用基因组数据进行进化分析是科学应对COVID-19大流行的重要组成部分，COVID-19是由严重急性呼吸综合征冠状病毒2 （SARS-CoV-2）引起的。利用采样时间和地点信息推断病毒样本的进化史或系统发育，使科学家能够估计病毒谱系在时间和地点上的分化。这些分析提供了采样事件之前的时间估计。有关突变和突变率的信息是这些系统发育分析所固有的，因此，如果存在特定的突变率加快的病毒谱系，则可以识别出来。此外，分子系统动力学不仅包括进化历史，还包括病毒遗传变异和病毒种群动态的信息，这些都是在地理和时间的背景下进行的。该项目的软件将用于SARS-CoV-2研究：移动和迁移模式；爆发起源时间；突变率和对健康有潜在影响的重大突变的检测；在不同地理范围的人群中的流行情况；生育数量及其对政策的影响；感染病例报告率。也许最直接的影响是，该项目的软件将加速追踪和确定接触者追踪无效的特定地理区域的疫情起源。接触追踪和系统发育分析在不同的尺度上工作，因此是互补的。它们共同提供了对当前大流行传播模式的更全面的看法。系统动力学分析在推论方面尤其丰富，尽管需要相当大的计算成本。本项目将大大加快对新冠肺炎数据集的系统发育和系统动力学分析，并促进其在美国国家科学基金会支持的计算资源、学术计算中心和云计算环境上的计算。具体活动包括：设计新的策略，对以SARS-CoV-2为重点的病毒爆发的大型数据集进行高效并行计算；制定策略，消除阻碍高效使用并行系统发育和系统动力学分析的障碍；开发算法，在图形处理单元（gpu）上实施这些新策略；以及与他人合作，缩短分析SARS-CoV-2数据集获得结果的时间。该RAPID奖由生物基础设施部使用《冠状病毒援助、救济和经济安全法案》的资金颁发。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Evolutionary analyses using genomic data are an essential component of the scientific response to the COVID-19 pandemic, which is caused by Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). Inferring the evolutionary history, or phylogeny, of virus samples with sampling time and location information allows scientists to estimate the divergence of viral lineages in time and place. These analyses provide time estimates that predate sampling events. Information about mutations, and the rate of mutation, is inherent to these phylogenetic analyses such that specific viral linages with accelerated mutation rates, if they exist, can be identified. Furthermore, molecular phylodynamics includes not only evolutionary history but also information on viral genetic variation and viral population dynamics, again all in the context of geography and time. The software from this project will be used in SARS-CoV-2 research on: patterns of movement and migration; time of outbreak origin; rate of mutation and detection of significant mutations with potential health impact; prevalence in populations at different geographical scales; reproductive number and impact on policy; and infection-to-case reporting rates. Perhaps of most immediate impact is that software from this project will accelerate tracing and dating the origins of outbreaks in specific geographic regions where contact tracing is not effective. Contact tracing and phylogenetic analyses work on different scales, and thus are complementary. Together they provide a more comprehensive view of the transmission patterns for the current pandemic.Phylodynamic analyses are particularly rich in terms of inferences, albeit at a considerable computational cost. This project will greatly accelerate phylogenetic and phylodynamic analysis of SARS-CoV-2 data sets, and facilitate their computation on National Science Foundation supported computing resources, academic computing centers, as well as cloud computing environments. Specific activities include designing new strategies for efficient parallel computation of large data sets from viral outbreaks focusing on SARS-CoV-2, developing strategies for removing the barriers to easy use of highly performant parallel phylogenetic and phylodynamic analyses, developing algorithms for implementing these new strategies on graphical processing units (GPUs), and working with others to improve the time to results for analyses of SARS-CoV-2 data sets. This RAPID award is made by the Division of Biological Infrastructure using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.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.