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Published on: December 23, 2020
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Temporal epistasis inference from more than 3 500 000 SARS-CoV-2 genomic sequences.
Hong-Li Zeng1, Yue Liu1, Vito Dichio2,3
1School of Science, Nanjing University of Posts and Telecommunications, New Energy Technology Engineering Laboratory of Jiangsu Province, Nanjing 210023, China.
Physical Review. E
|November 18, 2022
Summary
Direct coupling analysis (DCA) reveals how mutations in SARS-CoV-2 interact over time. These epistatic interactions are more stable than correlations and highlight key mutations in the spike protein.
Area of Science:
- Genomics
- Virology
- Computational Biology
Background:
- Understanding viral evolution requires analyzing genetic interactions.
- SARS-CoV-2 evolution involves complex mutation dynamics.
- Epistatic interactions influence viral adaptation and fitness.
Purpose of the Study:
- To investigate epistatic interactions in SARS-CoV-2 using Direct Coupling Analysis (DCA).
- To analyze the temporal stability of these interactions.
- To identify specific mutations involved in epistatic interactions.
Main Methods:
- Utilized Direct Coupling Analysis (DCA) on over 3.5 million SARS-CoV-2 genomes from GISAID (up to Oct 2021).
- Segmented genomic data by month of sampling to track temporal changes.
- Compared DCA with correlation methods to assess their strengths and weaknesses.
Main Results:
- DCA terms demonstrate greater temporal stability compared to simple correlations.
- Epistatic interactions identified by DCA change over time as mutations emerge, fixate, or disappear.
- Correlations are influenced by phylogenetic effects and short-range genomic dependencies, while DCA reveals long-range interactions.
- Putative epistatic interactions were identified in the spike protein locus.
Conclusions:
- DCA is a valuable tool for dissecting complex epistatic interactions in rapidly evolving viruses like SARS-CoV-2.
- Temporal analysis of DCA provides insights into the dynamic nature of viral evolution.
- Findings contribute to understanding the genetic basis of SARS-CoV-2 adaptation and potential therapeutic targets.
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