The Implementation Of Computational Statistics In Molecular Phylogenetics To Identify Lineage Diversity Through Viral Genome Sequences (Case study: severe acute respiratory syndrome coronavirus 2)

Abstract

COVID-19 is one of the global problems in this biennial period. The cause is severe acute respiratory syndrome coronavirus-2. This study used n = 60 viral genome from other countries, including Indonesian samples. The goals of this research are knowing the evolutionary relationship between viral genomes from and the development of SARS-CoV-2 variants through the results of phylogenetic tree reconstruction with the application of the maximum-likelihood method in molecular phylogenetic and provide biological insight through the studied viral genome regarding the SARS-CoV-2 variant. This research uses several software such as Jalview, MAFFT, MEGA-X, RAxML GUI 2.0, and iTOL v.5. This secondary data was obtained through GISAID. This study uses the maximum likelihood method, with the substitution model for DNA is GTR+G+I. The results of the analysis show that Clade L, S, and O are in one cluster. Clade G and GV are also in one cluster. Then followed by other clade clusters such as GH and GR. One thing that is interesting is that the characteristics of the GK clade are also owned by the O clade, both of which are in the same variant, VOC Delta. Clade L can be used as a reference for samples with different clades and Clade G can be said to be the parent of other fractional clades, such as GK, GR, GV, and others. Some samples also show that some samples have Indonesian ancestry. From the case studies, there are possible local cases, possible imported cases, and imported cases.