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Updated: Mar 23, 2026

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

Sudhir Kumar¹, Glen Stecher², Koichiro Tamura³

¹Institute for Genomics and Evolutionary Medicine, Temple University Department of Biology, Temple University Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia.

Molecular Biology and Evolution

|March 24, 2016

Summary

This summary is machine-generated.

The updated Molecular Evolutionary Genetics Analysis (Mega) software now supports 64-bit systems for analyzing large genomic datasets. This version enhances phylogenomic research with new tools for timetree construction and gene duplication prediction.

Keywords:

evolution.gene families software timetree

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Area of Science:

Bioinformatics
Computational Biology
Evolutionary Genetics

Background:

The Molecular Evolutionary Genetics Analysis (Mega) software is a widely used tool for evolutionary biology research.
Previous versions had limitations in handling large datasets due to 32-bit architecture.
Advancements in computing power necessitate software optimization for modern biological data analysis.

Purpose of the Study:

To introduce the latest version of Mega software with significant performance and feature enhancements.
To enable the analysis of substantially larger biological datasets.
To provide advanced functionalities for phylogenomic and phylomedicine studies.

Main Methods:

Optimization of Mega software for 64-bit computing systems.
Development of an advanced wizard for constructing phylogenetic timetrees.
Implementation of automated gene duplication event prediction in gene family trees.

Main Results:

The 64-bit Mega software efficiently analyzes datasets containing tens of thousands of sequences.
New functionalities streamline the process of molecular clock estimation and gene family evolution analysis.
Both graphical user interface (GUI) and command-line versions are available for diverse user needs.

Conclusions:

The latest Mega version significantly enhances capabilities for large-scale phylogenomic and phylomedicine research.
The software's optimization and new features facilitate more in-depth evolutionary analyses.
Mega software remains a free, accessible, and powerful resource for the scientific community.