Analysis of The Nucleotide Sequence Diversity of the Lassa Virus and Augmenting its Phylogenetic Tree
Author(s) -
Sean Oddoye
Publication year - 2018
Publication title -
stem fellowship journal
Language(s) - English
Resource type - Journals
ISSN - 2369-0399
DOI - 10.17975/sfj-2018-005
Subject(s) - lassa fever , phylogenetic tree , genbank , biology , virology , viral quasispecies , nucleotide diversity , mega , genetic diversity , lassa virus , population , evolutionary biology , genetics , tree (set theory) , virus classification , phylogenetics , virus , genome , genotype , medicine , gene , hepatitis c virus , environmental health , mathematical analysis , physics , mathematics , astronomy , haplotype
Lassa Virus (LASV) is the etiological catalyst for Lassa fever, an acute hemorrhagic disease with a mortality rate of 15%. Many aspects of the Lassa virus are not understood, like the causation of deafness in ⅓ of surviving patients or why symptoms are benign for 80% of those infected with the virus. Ambiguities like these suggest that there might exist some genomic heterogeneity among infecting viruses and demonstrate a need to quantify and analyze polymorphisms within LASV. Patterns that emerge from phylogenetic trees can be used to assess the structure of a population while also providing insights to the genetic makeup. The purpose of this investigation was to develop a more streamlined means of calculating nucleotide diversity within a subpopulation of Lassa virus strains and to augment a phylogenetic tree of the Lassa Virus glycoprotein precursor (GPC) segment. A total of 25 partial and complete data sequences of LASV strains were obtained from the Genbank Archives. During phase one of this investigation, the sequence data was inputted into MEGA analytical software and the sequence diversity was derived on a nucleotide level. Data from the individual strand sequences was used to augment a phylogenetic tree using Treeview X software. In phase two of this investigation, an algorithm was created using RStudio, with BSGenome and BioStrings extensions. The sequence diversity derived from the statistical analyses on MEGA was compared to that of the algorithm created. A p-value of 0.08 was found, which deviates from the accepted range of non-medical p-value of 0.00 to 0.05. It is suggested that future research focuses on creating a refurbished version of the algorithm to calculate a nucleotide diversity within a percent error of 5%.
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