| NSF Org: |
CCF Division of Computing and Communication Foundations |
| Recipient: |
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| Initial Amendment Date: | May 4, 2020 |
| Latest Amendment Date: | May 4, 2020 |
| Award Number: | 2027669 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Mitra Basu
mbasu@nsf.gov (703)292-8649 CCF Division of Computing and Communication Foundations CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | May 15, 2020 |
| End Date: | April 30, 2021 (Estimated) |
| Total Intended Award Amount: | $100,000.00 |
| Total Awarded Amount to Date: | $100,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
506 S WRIGHT ST URBANA IL US 61801-3620 (217)333-2187 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
506 S. Wright Street Urbana IL US 61801-2302 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | COVID-19 Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
To facilitate real-time outbreak management and mitigation strategies, there is an urgent need to understand the spread of COVID-19. Researchers reconstruct the evolutionary and transmission history of the virus by applying algorithms to sequencing samples of COVID-19 patients. However, a key challenge is the presence of multiple strains of the virus within hosts, which is overlooked by current algorithms. This RAPID project will improve the nation?s COVID-19 response by developing algorithms to characterize the ongoing evolution and spread of the viral strains that coexist within patients. The developed algorithms will be applicable to future disease outbreaks.
This RAPID project seeks to understand the impact of within-host viral diversity on the current spread of COVID-19. The project will identify the viral strains coexisting in patients through the development of algorithms that deconvolve COVID-19 sequencing samples. Subsequently, the project will assess whether or not such coexisting strains are the result of multiple infection events. Finally, the project will quantify the severity of the identified viral strains through a protein functional analysis of their mutations. Results will be disseminated through an online portal that enable labs and hospitals to upload their sequencing reads and generate annotations and characterizations of COVID-19 viral strains.
In summary, the goal of this research is to understand SARS-CoV-2 by investigating the evolutionary origins of the virus and its genetic variation within host species in order to determine how molecular variation correlates with host range, and to evaluate risk of further disease emergence.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
To facilitate real-time outbreak management and mitigation strategies, there is an urgent need to understand the spread of COVID-19. Researchers reconstruct the evolutionary and transmission history of the virus by applying algorithms to sequencing samples of COVID-19 patients. However, a key challenge is the presence of multiple variants of the virus within hosts, which is overlooked by current algorithms. This RAPID project sought to improve the nation’s COVID-19 response by developing algorithms to characterize the ongoing evolution and spread of the viral variants that coexist within patients. The developed algorithms will be applicable to future disease outbreaks. Beyond SARS-CoV-2, this project also sought novel algorithms to reconstruct transcriptomes of coronaviruses and identify regulatory sequences within coronavirus genomes.
This RAPID project has supported the development of:
- Algorithms and theory to reconstruct multi-strain/multi-variant infections given a timed phylogeny and additional epidemiological data.
- Pipeline for SARS-CoV-2 sequence analysis.
- Algorithms and theory for reconstruction of coronavirus transcriptomes.
- Tool for generating SARS-CoV-2 variant-specific primers.
The tool takes as input GISAID sequences of SARS-CoV-2 viruses from COVID-19 patients from around the world, a set of target sequences, and a lineage of interest. The tool then computes for each input target sequence, as well as combinations of input sequences, the sensitivity and specificity for identifying the lineage of interest as a function of time. - Algorithms and theory to identify core and transcription regulatory sequences of coronavirus genomes.
Last Modified: 09/02/2021
Modified by: Mohammed El-Kebir
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