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Surveillance genome sequencing to detect SARS-CoV-2 virus variants in Montana

Surveillance genome sequencing to detect SARS-CoV-2 virus variants in Montana
监测基因组测序以检测蒙大拿州的 SARS-CoV-2 病毒变异
批准号:
10595197
负责人:
BRUCE E BOWLER
金额:
$6.1万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-08-10 至 2026-07-31

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中文摘要
翻译
项目摘要 蒙大拿州是一个地理面积很大、以农村为主的州,有12个部落民族。从……开始 SARS-CoV-2大流行一直持续到2021年春季,蒙大拿州在全国范围内的代表性严重不足 测序数据库--尤其是在农村地区--限制了该州追踪和控制 横跨城乡鸿沟的大流行病。在NIGMS的支持下,UM Cobre生物分子中心 结构与动力学(CBSD)与蒙大拿州公共卫生与公共服务部合作 (DPHHS)和其他地区卫生合作伙伴对超过2,650个SARS-CoV-2全基因组进行测序 过去11个月。这相当于蒙大拿州所有可公开获得的SARS-CoV-2序列数据的约20%, 导致蒙大拿州在国家测序数据库中的比例过高, 在以农村为主、包含部落民族的地区进行更深层次的抽样。各种时间序列的可获得性 过去一年产生的基因组数据提供了现在填补有关 跨越城乡鸿沟的SARS-CoV-2多样性和进化。转变为分析密集型阶段 该项目是CBSD Cobre赠款的补充,将继续支持人类基因组测序 新病例,同时开发复杂的群体遗传模型,以严格测试适应性病毒 在州和地区内抽样的遗传多样性序列模式的进化。我们的团队是多元化的 在生物信息学、种群遗传学、宿主-微生物相互作用和药物遗传学方面的专业知识将使 美国将模拟蒙大拿州SARS-CoV-2基因组变异与全球SARS-CoV-2变化的比较 随时间变化的多样性。现有数据的广度使分析能够专注于跟踪存在和 已知的SARS-CoV-2变种在城乡差距中的频率,同时也监测 新的变种。通过利用我们在系统基因组学和种群遗传学方面的独特专业知识,建议的 研究将建立分析框架和模型,重点解开人口和自然 选择相互作用,塑造SARS-CoV-2基因组进化。这项补充资料将透过 第三阶段CBSD Cobre奖,有三个具体目标: 目标1:通过以下途径,蒙大拿州社区中SARS-CoV-2变异的遗传结构是什么 时间以及这种变异与区域、国家和全球SARS-CoV-2的多样性相比如何? 目标2:农村和农村之间流行的SARS-CoV-2变异株的基因组成是否有所不同 蒙大拿州的大都市社区? 目标3:局部或区域频率显著升高的突变是否反映了适应性病毒 进化论? 总体而言,该项目将为SARS-CoV-2在农村州的传播动态提供关键的新见解, 同时开发可广泛应用于全球监督组织的复杂分析模型。
英文摘要
Project Summary Montana is a geographically large and predominantly rural state with 12 Tribal nations. From the beginning of the SARS-CoV-2 pandemic through the spring of 2021, Montana was severely under-represented in national sequencing databases—and specifically in rural areas—limiting the state’s ability to track and control the pandemic across the urban-rural divide. With NIGMS support, the UM COBRE Center for Biomolecular Structure and Dynamics (CBSD) teamed with the Montana Department of Public Health & Human Services (DPHHS) and other regional health partners to sequence over 2,650 whole SARS-CoV-2 genomes over the last 11 months. This represents ~20% of all publicly-available SARS-CoV-2 sequence data from Montana and has resulted in Montana now being proportionally over-represented in national sequencing databases, with deeper sampling in predominantly rural areas that contain Tribal nations. The availability of diverse time-series genome data produced over the last year provides the opportunity to now fill critical gaps in knowledge about SARS-CoV-2 diversity and evolution across the urban-rural divide. Shifting to an analysis-intensive phase of the project, this supplement to the CBSD COBRE grant will continue to support whole genome sequencing of new cases while also developing sophisticated population genetic models to rigorously test for adaptive viral evolution across serial patterns of genetic diversity sampled within the state and the region. Our team’s diverse expertise in bioinformatics, population genetics, host-microbe interactions, and pharmacogenetics will enable us to model how SARS-CoV-2 genomic variation in Montana compares to changes in global SARS-CoV-2 diversity through time. The breadth of existing data allows for analyses focused on tracking the presence and frequency of known SARS-CoV-2 variants of concern across the urban-rural divide, while also surveilling for new variants. By leveraging our unique expertise in phylogenomics and population genetics, the proposed research will establish analytical frameworks and models focused on unraveling how demography and natural selection interact to shape SARS-CoV-2 genome evolution. This supplement will be implemented through the phase III CBSD COBRE award and has three specific aims:  Aim 1: What is the genetic structure of SARS-CoV-2 variation across Montana communities through time and how does this variation compare to regional, national, and global SARS-CoV-2 diversity?  Aim 2: Does the genetic composition of circulating SARS-CoV-2 variants differ between rural versus metropolitan communities in Montana?  Aim 3: Do mutations with significantly elevated local or regional frequencies reflect adaptive viral evolution? Overall, the project will provide critical new insights into the dynamics of SARS-CoV-2 spread in a rural state, while developing sophisticated analytical models that can be broadly applied by global surveillance groups.
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