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

  • Funded by National Science Foundation (NSF)
  • Total publications:6 publications

Grant number: 2125664

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Key facts

  • Disease

    COVID-19
  • Start & end year

    2021
    2023
  • Known Financial Commitments (USD)

    $300,000
  • Funder

    National Science Foundation (NSF)
  • Principal Investigator

    Jason Ernst
  • Research Location

    United States of America
  • Lead Research Institution

    University of California-Los Angeles
  • Research Priority Alignment

    N/A
  • Research Category

    Pathogen: natural history, transmission and diagnostics

  • Research Subcategory

    Pathogen genomics, mutations and adaptations

  • Special Interest Tags

    N/A

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

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.

Publicationslinked via Europe PMC

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ChromGene: gene-based modeling of epigenomic data.

Universal chromatin state annotation of the mouse genome.

A framework for group-wise summarization and comparison of chromatin state annotations.

Universal annotation of the human genome through integration of over a thousand epigenomic datasets.

Single-nucleotide conservation state annotation of the SARS-CoV-2 genome.