Epidemiological associations with genomic variation in SARS-CoV-2
Ali Rahnavard1, Tyson Dawson2, Rebecca Clement2
1Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA. rahnavard@gwu.edu.
Scientific Reports
|November 27, 2021
Summary
SARS-CoV-2 evolves rapidly, with its Spike (S) and nonstructural protein 3 (nsp3) showing the most genomic variation. This variation correlates with geographic origin and time, aiding in tracking viral spread and predicting outcomes.
Area of Science:
- Virology
- Genomics
- Epidemiology
Background:
- Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) drives the ongoing COVID-19 pandemic.
- The virus continuously evolves, presenting challenges to immune responses and interventions.
- Understanding SARS-CoV-2 genomic variation is crucial for effective public health strategies.
Purpose of the Study:
- To analyze SARS-CoV-2 genomic regions for associations with epidemiological data.
- To identify key viral features driving genomic variation.
- To develop a metric for assessing viral diversity and spread.
Main Methods:
- Division of the SARS-CoV-2 genome into 29 regions for analysis.
- Application of novel analytical approaches to correlate genomic features with epidemiological metadata.
- Development and application of a new statistic, 'coherence,' to measure viral phylogenetic diversity.
Main Results:
- Nonstructural protein 3 (nsp3) and Spike (S) proteins exhibit the highest genomic variation and correlate strongly with whole-genome variation.
- Spike protein variation is linked to variations in nsp3, nsp6, and 3'-to-5' exonuclease.
- Geographic origin and pandemic duration were the most significant metadata influencing genomic variation; host sex and age were least influential.
- The 'coherence' statistic identified geographic areas with high and low viral diversity, highlighting potential hotspots and isolated regions.
Conclusions:
- Genomic variation in SARS-CoV-2 is significantly influenced by geographic factors and time.
- The Spike protein and nsp3 are critical targets for understanding viral evolution.
- The novel 'coherence' metric can inform public health interventions by mapping viral spread and diversity.
- Findings can guide the prioritization of genes for predicting health outcomes and improving diagnostic tests.
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