UNDERSTANDING EVOLUTIONARY RELATIONSHIPS AND ANALYSIS METHODS THROUGH MEGA SOFTWARE

Abstract

In recent years, genome sequencing has been a highly effective tool to investigate a wide range of biological systems. Numerous steps for the interpretation of raw sequence data require comparative analysis of molecular sequences for each time period to reveal functional genome differences.  Molecular Evolutionary Genetics Analysis (MEGA), a user-friendly software developed to analyse DNA and protein sequence data, provides a set of tools to perform these analyses. MEGA enables a wide range of investigations such as combining sequence alignments, constructing evolutionary trees, estimating genetic distances and variations, and uncovering ancestral sequences. There are some bioinformatics methods to estimate the past knowledge of organisms from their current knowledge. The phylogenetic tree is similar to the evolutionary tree in terms of relationships between biological entities, and the relationships between various species, organisms, genes, etc. in the phylogenetic tree structure are shown by dendograms. Analyses can be performed on nucleic acid, protein, DNA and RNA sequences. There are basically two trees: rooted and unrooted phylogenetic trees. The root is represented by the rooted phylogenetic tree type and is not represented in the unrooted tree, but it can be considered as a root tree because some characters are mapped to the data used. The common ancestor is represented by the root of the phylogenetic tree and the branches of the nodes in the tree represent recent biological information. MEGA software was used to estimate the relationships shown in this figure. In this study, phylogenetic tree construction and evolutionary roots detection and analysis methods were investigated through MEGA 11 software programme on a working file containing data of 10 strains (KC710304.1, KC710305.1, KC710306.1, KC710307.1, KC710308.1, KC710309.1, KC710310.1, KC710311.1, KC710312.1 and KC710313.1) of Thermoplasma acidophilum bacteria obtained from NCBI data bank.