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Visualization of SARS-CoV-2 using Immuno RNA-Fluorescence In Situ Hybridization
Published on: December 23, 2020
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.
Abstract:
We use direct coupling analysis (DCA) to determine epistatic interactions between loci of variability of the SARS-CoV-2 virus, segmenting genomes by month of sampling. We use full-length, high-quality genomes from the GISAID repository up to October 2021 for a total of over 3 500 000 genomes. We find that DCA terms are more stable over time than correlations but nevertheless change over time as mutations disappear from the global population or reach fixation. Correlations are enriched for phylogenetic effects, and in particularly statistical dependencies at short genomic distances, while DCA brings out links at longer genomic distance. We discuss the validity of a DCA analysis under these conditions in terms of a transient auasilinkage equilibrium state. We identify putative epistatic interaction mutations involving loci in spike.
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