Community Structure and Temporal Dynamics of Viral Epistatic Networks Allow for Early Detection of Emerging Variants with Altered Phenotypes

In this study, we demonstrated that SARS-CoV-2 emerging variants can be detected or predicted by examining the community structure of viral coordinated substitution networks. These variants can be linked to dense network communities, which become discernible earlier than their associated viral variants reach noticeable prevalence levels. From these insights, we developed HELEN (Heralding Emerging Lineages in Epistatic Networks), a computational framework that identifies densely connected communities of SAV alleles and merges them into haplotypes using a combination of statistical inference, population genetics, and discrete optimization techniques. Our methodology can be employed to detect emerging and circulating strains of any highly mutable pathogen with adequate genomic surveillance data, while offering greater scalability than phylogenetic lineage tracing methods.