MEGA: A Bio Computational Software for Sequence and Phylogenetic Analysis

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Abstract—In the last five years, Biocomputing has moved
into central position in molecular biology research. Enormous
improvements in genetic mapping and sequencing technology
have led to the accumulation of vast amount of biological
information in the database. With the advent of this extensive
repertoire of raw sequence information, the next major
challenge for a modern researcher is to interpret this biological
information. At the remarkable rate of progress that is being
made in sequencing and phylogenetic organisms, wet research
techniques alone cannot keep up with the influx of genomic
information. Molecular Evolutionary
(MEGA) is user friendly bio-computational software for
sequence analysis and phylogenetic analysis.

MEGA developed with the aim to bridge the gap between wet
lab result and significance that can characterize by nucleotide
and amino acid to produce scoring and evolutionary
relationship. In this paper an attempt had been made to analysis
the growth and evolution of MEGA software from MEGA1 to
MEGA 4 and its advantages over other bioinformatics tool box.


Index Terms—Biocomputing, Sequence Alignment, Scoring,
MEGA

Genetic Analysis
I. INTRODUCTION
MEGA is software tool with the functional task of providing
annotation of biologically relevant information from a
nucleotide or proteomic sequence. Its’ goal is to provide a
simple but powerful interface for the analysis and mining of
genomic information while seamlessly handling the
nonscientific complexities of interfacing with hardware,
computational clusters, software packages, raw data, and file
formats.
The design of the MEGA software package (Molecular
Evolutionary Genetic Analysis) is engineered to be an
‘extensible framework’ that facilitates expansion with any
bioinformatics software tool approaching point and click
simplicity. MEGA 4 is specifically designed to reduce the
time needed for mundane tasks in data analysis and to
provide statistical methods of molecular evolutionary genetic
analysis. MEGA 4 also includes distance matrix and

Manuscript received 10 Januarary, 2009 This work was supported in part
by the Department of Chemical Engineering & Bio Technology.
1. Vipan Kumar ,Senior Lecturer, Department of Chemical Engineering &
Bio-Technology ,Gurdaspur-143521,Punjab.India (corresponding
author to phone:91-98882-20918; fax:91-1874-221463; e-mail:
vipan752002@ indiatimes.com )
2. Apurba Dey Dr., Professor, Department of Biotechnology, NIT,
Durgapur, West Bengal, India (e-mail:apurbadey2003@yahoo.co.in).
3. Amarpal Singh Dr. Department of Electronics Engineering &
Communication, Gurdaspur-143521,Punjab.India
(e-mail:a_singh@yahoo.com).
phylogeny explorers well as advanced graphical modules for
the visual representation of input data and output result.
II. LITERATURE REVIEW & EVOLUTION OF MEGA
MEGA VERSION 1
The first version of MEGA (1994) made many methods of
evolutionary analysis easily accessible to the scientific
community for research and education.MEGA1 was
developed keeping in mind the limited computational
resources available on the average personal computer (RAM)
in the early 1990. MEGA1 launched without sophisticated
features because low memory of the system. It exclude
Sequence alignment construction (alignment editor, Motif
searching and BLAST sequences from alignment), multiple
sequence alignment, substitution pattern homogeneity test
(Monte Carlo test) and Synonymous/Non-synonymous
(Modified Nei-Gojobori method).In addition of that
UPGMA, part of phylogeny is not considered in version
1.Moreover the MEGA 1 used the DOS operating platform.

MEGA Version 2

As compared to the first version, MEGA2 contains a more
extensive collection of methods to estimate the number of
synonymous/Non-synonymous
synonymous site and non-synonymous substitutions
respectively. MEGA 2 had added the modified Nei-Gojobori
method as well as Li-Wu-Lou methods and its modification.
MEGA 2 expanded with the choice of tree building methods
keeping in mind that the future data sets will likely consist of
a large number of sequences from multiple genes. UPGMA,
Neighbor-Joining, Maximum evolution and maximum
parsimony methods are also included in this version.
Molecular evolutionary genetic analysis version 2 broadly
has capabilities (1) analyses of large dataset (2) creation and
analysis’s of groups of sequences (3) expanding the
repertoire of statistical methods for molecular evolutionary
studies (4) new modules for visual representation of input
data and output results on Microsoft window platform.
A survey of the research papers citing the use of MEGA
reveals that it has been utilised in diverse disciplines,
including AIDS/HIV research, virology, bacteriology and
general disease, plant biology, conservation biology,
systematics, developmental evolution and population
genetics.

MEGA Version 3

The newly released MEGA3 expands the functionalities of
MEGA2 by adding sequence data alignment and assembly
substitutions per
MEGA: A Bio Computational Software for
Sequence and Phylogenetic Analysis
Vipan Kumar1, Apurba Dey2, Amarpal Singh3
Proceedings of the World Congress on Engineering 2009 Vol II
WCE 2009, July 1 - 3, 2009, London, U.K.
ISBN:978-988-18210-1-0WCE 2009

Page 2

features, along with other advancements. The sequence data
acquisition is now effectively integrated with the
evolutionary analyses, making it much easier to conduct
comparative analyses in
environment. MEGA3 is not trial to be a catalogue of
evolutionary analysis methods. Rather, it is for exploring
sequence data from evolutionary perspectives, constructing
phylogenetic trees, and testing evolutionary hypotheses,
especially for large-scale data sets that have been generated
by recent genomics projects. The advantages of MEGA 3 are
the sequence alignment and data assembly modules – as they
constitute the first step in any comparative sequence analysis
investigation.

This is followed by descriptions of the different types of data
that MEGA can analyze its graphical input and output data
explorers, dynamic data sub setting facilities, and the
statistical methods and computational tools available for
inferring phylogenetic trees and estimating evolutionary
distances.

MEGA Version 4

The fourth version (MEGA4) contains three distinct newly
developed functionalities, Firstly, a Caption Expert software
module that generates descriptions for every result obtained
by MEGA4. This description informs the user of all of the
options used in the analysis, including the data subset used
(e.g., codon positions included), the chosen option for the
handling of sites with gaps or missing data, the evolutionary
model of substitution (e.g., DNA substitution pat- tern,
uniformity of evolutionary rates among sites, and
homogeneity assumption among lineages), and the methods
applied for estimating pairwise distances and for inferring
and testing phylogeny. The caption also includes specific
citations for any method, algorithm, and software used in the
given analysis. The significance of this description is
promote a better understanding of the underlying
assumptions used in analyses, and of the results produced.
This is needed because MEGA’s intuitive graphical interface
makes it easy for both new and expert users to
conduct a variety of computational and statistical analyses.

Second, MEGA 4 added a Maximum Composite Likelihood
(MCL) method for estimating evolutionary distances (dij)
between DNA sequences, which MEGA users frequently
employ for inferring phylogenetic trees, divergence times,
and average sequence divergences between and within
groups of sequences. In this approach, the Composite Log
Likelihood (CL) obtained as the sum of log likelihood for all
sequence pairs in an alignment is maximized by fitting the
common parameters for nucleotide substitution pattern (h) to
every sequence pair (i,j).The MCL approach differs from
current approaches for evolutionary distance estimation,
wherein each distance is estimated independently of others,
either by analytical formulas or by likelihood methods
(independent estimation [IE] approach).The MCL method
has many advantages over the IE approach. To begin with,
the IE method for estimating evolutionary distance for each
pair of sequences will often cause rather large errors unless
very long sequences are used. The use of the MCL method
reduces these errors considerably, as a single set of
an integrated computing
parameters estimated from all- sequence pairs is applied to
each distance estimation.

Third, we have now programmed MEGA4 to run on some
versions of Linux through the Wine software compatibility
layer. The first advancement alleviates the problem of
performance degradation (and the need to purchase Windows
emulation software) when using MEGA on Linux. Wine is
neither a hardware nor a software emulator, but an open
source tool that allows for the native execution of Windows
applications on Linux. MEGA4 running on Linux show the
display, stability, and performance to be highly satisfactory
and comparable to the native Windows system .Further more,
investigators now report MEGA4 running on Intel-based
Macintosh computers under the Parallels program as well as
it does on Windows-native personal computers .The Parallels
program is a native solution for Macintosh computers that
permits them to simultaneously run Windows and Macintosh
software.

MEGA 4 also support for a multi-user environment, which
will allow each user of the same computer to keep his/her
customized settings, including file locations, window sizes,
choice of genetic code table, and previously used analysis
options. This feature will facilitate educational and
laboratory usage, where a single computer is often shared by
multiple users. In conclusion, MEGA4 now contains a wide
array of functionalities for the molecular evolutionary
analysis
III. METHOD

We are utilizing a series of techniques for the prediction of
specific characteristics of proteins and nucleotide. Each
analysis package is treated as a modularized component that
can be dynamically incorporated in MEGA to facilitate
extensibility and allow updating output data for research of
sequence alignment (pair-wise and multiple) and new
methods are developed for evolutionary analysis.

Figure1: Working Model of MEGA Software



Proceedings of the World Congress on Engineering 2009 Vol II
WCE 2009, July 1 - 3, 2009, London, U.K.
ISBN:978-988-18210-1-0WCE 2009

Page 3

IV. APPROACH
Included in the initial release of MEGA, software have
developed or incorporated existing modules for the analysis
of the following qualities:
- Creating Multiple Sequence Alignment
- Sequence Conversion from Nucleotide to Protein
- Computing Basic Statistical Quantities for Sequence Data
- Constructing Phylogenetic Trees
- Distance Matrix Explore
- Physiological / Chemical characteristics
- Computing Evolutionary Distance
- Synonymous and Non-synonymous Test
Details as to the nature of modules, external resources,
databases and software tools incorporated in the MEGA are
listed as a web resource.


V. IMPLEMENTATION
MEGA is composed of three individual separate
components, namely - A graphical user interface, a
processing engine, and a report engine. The graphical user
interface provides the control point that the user interacts
with on a personal computer. This component is developed
to be run on any desktop computer (Macintosh –Windows
using Virtual PC, Sun Workstation-Soft Windows 95 and
Linux-Window using VMWare) using a multiplatform for
uniformity.

The processing engine is authenticate, manages the forking
and execution of individual analyses or generation of shell
scripts for the intelligent submission to a processing
queue. Queues currently supported are National Centre for
Biotechnology Information (NCBI), Clustal, Blast and Fasta.

The report engine combines resulting output to attempt to
interpret make intelligent summaries along with presenting
the raw analyses output in a failure format. Moreover, a user
can specify and filter for specific characteristics of amino
acids and nucleic sequence, which enable a user to utilize
MEGA as user friendly search tool.

VI. CONCLUSION

In conclusion, MEGA4 now contains a wide array of
functionalities for the molecular evolutionary analysis of data
(http://www.megasoftware.net/features.html). It is useful to
note that while MEGA latest version is continuously adding
new methods and functions up to MEGA 4. MEGA, not
intend to make it a catalog of all evolutionary analysis
methods available. Rather, it is anticipated to become a
workbench for the exploration of sequence data from
evolutionary perspectives. MEGA have produced the
foundation of a powerful, easy to use, extensible software
package that is able to make a working hypothesis of
characteristics of a sequence and evolutionary analysis.
MEGA produces annotation results that are interpreted by
computer and presented in a useful manner, more so than
a conglomeration of separate analyses.


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through sequence
Proceedings of the World Congress on Engineering 2009 Vol II
WCE 2009, July 1 - 3, 2009, London, U.K.
ISBN:978-988-18210-1-0WCE 2009