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EAGER: Understanding the genomes and strain mutations of SARS-CoV-2 and other viruses using comparative and population genetic approaches

EAGER: Understanding the genomes and strain mutations of SARS-CoV-2 and other viruses using comparative and population genetic approaches
EAGER:使用比较和群体遗传学方法了解 SARS-CoV-2 和其他病毒的基因组和毒株突变
批准号:
2125664
负责人:
Jason Ernst
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-05-01 至 2024-04-30

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中文摘要
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英文摘要
Comparative genomics provides a powerful lens in which to understand novel genomes. This EAGER award sees to gain a deeper scientific understanding of the genomes and strain mutations of SARS-CoV-2 and other viruses by developing and applying innovative comparative genomic and population genetic methods leveraging the expertise of the investigators in these areas. These analyses will elucidate the relative contributions of evolutionary forces that shape the SARS-CoV-2 genome and other virus genomes across deep and recent evolutionary time scales and will pinpoint functionally important positions in their genomes. They will inform efforts of the broader scientific community to model the dynamics of infection, strategies for mitigation, and to develop therapeutics. This research will be integrated into educational programs that leverage the BIG summer undergraduate research program and the Computational Genomics Summer Institute at UCLA.The specific aims are to develop and apply comparative genomic analyses for SARS-CoV-2 using multiple genome alignments of various coronavirus genomes. The work will leverage the recently developed ConsHMM method to annotate the SARS-CoV-2 genome at single nucleotide resolution into different conservation states. ConsHMM defines conservation states based on the combinatorial and spatial patterns of which species align to and match a reference genome using a multivariate hidden Markov model (HMM). These conservation states will be related to other annotations of the SARS-CoV-2 genome including (inter)genic and key protein regions. Population genetic approaches will be applied to publicly available sequences of the SARS-Cov-2 genome to infer fundamental properties of mutations. To estimate these parameters, novel structured coalescent-based models will be developed that account for demographic processes across multiple time points and locations. While the initial investigation will focus on the large collections of SARS-CoV-2 genomes that are becoming available, the methods developed will be applicable to the study of viral genomes (such as other coronaviruses, influenza, ebola, and HIV) and their strain mutations.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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1093/bioinformatics/btac722
发表时间: 2023-01-01
期刊: BIOINFORMATICS
影响因子: 5.8
作者: [Vu, Ha, Koch, Zane, Fiziev, Petko, Ernst, Jason]
通讯作者: Ernst, Jason
DOI: 10.1186/s13059-021-02572-z
发表时间: 2022-01-06
期刊: Genome biology
影响因子: 12.3
作者: [Vu H, Ernst J]
通讯作者: Ernst J
CAREER: Expanding the Dimensions of Computational Epigenomic Modeling and Analysis
  • 批准号:
    1254200
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $99.09万
  • 财政年份:
    2013
  • 负责人:
    Jason Ernst
  • 依托单位:
Postdoctoral Research Fellowships in Biology for FY 2009
  • 批准号:
    0905968
  • 项目类别:
    Fellowship Award
  • 资助金额:
    $12.3万
  • 财政年份:
    2009
  • 负责人:
    Jason Ernst
  • 依托单位:
国内基金
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  • 批准号:
    12005059
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