Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time

Area of Science:

• Virology
• Computational Biology
• Evolutionary Genetics

Background:

• Published SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) rooting and dating studies often assume a constant evolutionary rate and limited early genomic data from Wuhan.
• Empirical data and emerging evidence suggest these assumptions may be inaccurate, necessitating a re-evaluation of early SARS-CoV-2 evolution.

Purpose of the Study:

• To develop and apply an improved method for dating the common ancestor of SARS-CoV-2, accounting for evolutionary rate variation over time.
• To utilize large-scale genomic datasets to obtain more accurate estimates of the SARS-CoV-2 origin.

Main Methods:

• Extended a rapid rooting method to model evolutionary rate as a linear function, rather than a constant.
• Analyzed two large datasets of SARS-CoV-2 genomes (83,688 and 970,777 genomes) with complete sample collection dates.

Main Results:

• The improved method, modeling a changing evolutionary rate, provided more robust dating estimates compared to constant rate models.
• Dating of the SARS-CoV-2 common ancestor was estimated to be June 12, 2019, and July 7, 2019, using the two large genome datasets.
• Large datasets and rate variation modeling were crucial for overcoming high rate-heterogeneity across viral lineages.

Conclusions:

• The common ancestor of SARS-CoV-2 likely emerged earlier than previously estimated, potentially in mid-2019.
• Accurate dating of viral origins requires sophisticated models that account for evolutionary rate changes and comprehensive genomic data.
• The developed method, implemented in TRAD software, offers a more reliable approach for phylogenetic analysis of rapidly evolving viruses.