Infection Groups Differential (IGD) Score Reveals Infection Ability Difference between SARS-CoV-2 and Other Coronaviruses

The Corona Virus Disease 2019 (COVID-19) pandemic that began in late December 2019 has resulted in millions of cases diagnosed worldwide. Reports have shown that SARS-CoV-2 shows extremely higher infection rates than other coronaviruses. This study conducted a phylogenetics analysis of 91 representative coronaviruses and found that the functional spike protein of SARS-CoV-2, which interacts with the human receptor ACE2, is actually not undergoing distinct selection pressure compared to other coronaviruses. Furthermore, we define a new measurement, infection group differential (IGD) score, in assessing the infection ability of two human coronavirus groups. There are nine extremely high IGD (ehIGD) sites in the receptor-binding domain (RBD) out of 40 high IGD (hIGD) sites that exhibit a unique infection-related pattern from the haplotype network and docking energy comparison. These 40 hIGD sites are basically conserved among the SARS-CoV-2, i.e. there are only two hIGD sites mutated in four out of 1,058 samples, defined as rare-mutation hIGD (rhIGD) sites. In conclusion, ehIGD and rhIGD sites might be of great significance to the development of vaccines.

Structural and Genetic Analysis of Coronaviruses Spike Proteins Suggest Pangolin as a Proximate Intermediate Host of SARS-CoV-2 (COVID-19)

During December 2019, a novel coronavirus named SARS-CoV-2 has emerged in Wuhan, China. The human to human transmission of this virus has also been established. The virus has so far infected more than 2 million people and spread over 200 countries. The World Health Organization (WHO) has declared COVID-19 a global health emergency due to its spread well beyond China. It has been established that this virus originates from bats and uses an intermediate host for transfer to humans. The knowledge about the intermediate host is important to find the virus shuttle mechanism to stop future outbreaks. For this, the genetic and structural analysis of coronaviruses spike proteins was performed using a computer-assisted approach.To conduct the In silico analysis, 43 sequences of spike protein belong to different species were retrieved from the NCBI nucleotide database. Pairwise and multiple sequence alignments were performed to check the similarities and differences of the retrieved sequences. Moreover, to highlight relationships among different species, phylogenetics analysis was performed using the MEGA software tool. In the end, protein structure alignment (superimposition) was performed against the reference structure by UCSF Chimera software. The results highlighted that the maximum similarity of human protein was found against Bat and Pangolinsequences. Moreover, among Bat and Pangolin, the highest similarity was found against pangolin based on phylogenetics analysis. These results suggest that SARS-CoV-2 transfers from bats to humans through pangolins.

The Prevalence and Impact of Model Violations in Phylogenetics Analysis

In phylogenetic inference we commonly use models of substitution which assume that sequence evolution is stationary, reversible and homogeneous (SRH). Although the use of such models is often criticized, the extent of SRH violations and their effects on phylogenetic inference of tree topologies and edge lengths are not well understood. Here, we introduce and apply the maximal matched-pairs tests of homogeneity to assess the scale and impact of SRH model violations on 3,572 partitions from 35 published phylogenetic datasets. We show that many partitions (39.5%) reject the SRH assumptions, and that for most datasets, the topologies of trees inferred from all partitions differ significantly from those inferred using the subset of partitions that do not reject the SRH assumptions. These results suggest that the extent and effects of model violation in phylogenetics may be substantial. They highlight the importance of testing for model violations and possibly excluding partitions that violate models prior to tree reconstruction. They also suggest that further effort in developing models that do not require SRH assumptions could lead to large improvements in the accuracy of phylogenomic inference. The scripts necessary to perform the analysis are available in https://github.com/roblanf/SRHtests, and the new tests we describe are available as a new option in IQ-TREE (http://www.iqtree.org).