Computational Inference of Selection Underlying the Evolution of the Novel Coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2

Abstract

Coronaviruses are dangerous zoonotic pathogens; in the last 2 decades, three coronaviruses have crossed the species barrier and caused human epidemics. One of these is the recently emerged SARS-CoV-2. We investigated how, since its divergence from a closely related bat virus, natural selection shaped the genome of SARS-CoV-2. We found that distinct coding regions in the SARS-CoV-2 genome evolved under conditions of different degrees of constraint and are consequently more or less prone to tolerate amino acid substitutions. In practical terms, the level of constraint provides indications about which proteins/protein regions are better suited as possible targets for the development of antivirals or vaccines. We also detected limited signals of positive selection in three viral ORFs. However, we warn that, in the absence of knowledge about the chain of events that determined the human spillover, these signals should not be necessarily interpreted as evidence of an adaptation to our species.