MfSAT: Detect simple sequence repeats in viral genomes.

Abstract

Simple sequence repeats (SSRs) are ubiquitous short tandem repeats, which are associated with various regulatory mechanisms and have been found in viral genomes. Herein, we develop MfSAT (Multi-functional SSRs Analytical Tool), a new powerful tool which can fast identify SSRs in multiple short viral genomes and then automatically calculate the numbers and proportions of various SSR types (mono-, di-, tri-, tetra-, penta- and hexanucleotide repeats). Furthermore, it also can detect codon repeats and report the corresponding amino acid.

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Software

MfSAT: Detect simple sequence repeats in viral
genomes


Ming Chen2, 3, Zhongyang Tan1*, Guangming Zeng2, 3


1College of Biology, State Key Laboratary for Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082, China; 2College of Environmental
Science and Engineering, Hunan University, Changsha 410082, China; 3Key Laboratory of Environmental Biology and Pollution Control (Hunan University),
Ministry of Education, Changsha 410082, China; Zhongyang Tan - Email: zhongyang@hnu.cn; *Corresponding author


Received April 05, 2011; Accepted April 25, 2011; Published May 07, 2011


Abstract:
Simple sequence repeats (SSRs) are ubiquitous short tandem repeats, which are associated with various regulatory mechanisms and have been found in viral
genomes. Herein, we develop MfSAT (Multi-functional SSRs Analytical Tool), a new powerful tool which can fast identify SSRs in multiple short viral genomes
and then automatically calculate the numbers and proportions of various SSR types (mono-, di-, tri-, tetra-, penta- and hexanucleotide repeats). Furthermore, it also
can detect codon repeats and report the corresponding amino acid.


Keywords: comparative genomics, simple sequence repeat, software, microsatellite, codon repeat.


ISSN 0973-2063 (online) 0973-8894 (print)
Bioinformation 6(4): 171-172 (2011)
 

171 © 2011 Biomedical Informatics


Background:
Simple sequence repeats (SSRs) or microsatellites are tandemly repeated tracts
consisting of 1-6 base pair (bp) long units [1, 2]. Comprehensive analysis of
SSRs in 8619 pre-miRNAs indicates SSRs are widely present in these very
small non-coding RNA sequences [3]. It has been demonstrated that SSRs can
affect gene expression and the corresponding gene products and even cause
phenotypic changes or diseases [4, 5]. Correspondingly, computational tools
for detection of SSRs and their related information from whole genome
sequences are increasing as well [6]. The growing number of analytical tools
for SSRs has greatly assisted the understanding of SSRs at the genome-wide
level. Our examination of the available tools reveals certain faults. In order to
efficiently screen viral genome sequences for SSRs, we have developed a new
tool called MfSAT.

Methodology:
Consider a sequence or multiple sequences over a finite alphabet {(a, t, g, c) or
(a, u, g, c)}. A tract at a given locus will be defined as a microsatellite if that
tract can be expressed as a tandem repeat of a motif of 1–6 bp size [6]. Our
goal is to efficiently detect SSRs in a sequence or multiple sequences given an
arbitrary motif size or minimum repeat number. The proposed algorithm has
two parameters, maximum motif and minimum repeat number which are
independent. When you run according to the first parameter, the minimum
number is three, whereas if you run by use of another parameter, the maximum
motif is “hexa”. If users select the “Hexa?mono” tag, MfSAT progressively
scans for nucleation sites starting from hexanucleotide repeat to
mononucleotide repeat at a given locus. If no hexanucleotide repeat tract is
detected, then pentanucleotide repeat nucleation site will be searched for and so
on. This algorithm is the same with IMEx [6, 7]. However, if users select
another tag, “Mono?hexa”, in contrast to above step, in this section we
assume the algorithm advances the shortest repeats. Given a candidate
trinucleotide repeat motif k and its starting position j together with the starting
position d of coding sequence of analyzed genome sequences, the verification
formula determines whether an SSR is a codon repeat. The formula is as
follows:
S = (j-d)/3 (1)
If S is an integer, the trinucleotide repeat is a codon repeats. It remains to judge
what its corresponding amino acid is.

Software Requirements:
MfSAT can be used in any computer with windows system.

Input:
MfSAT uses a advanced and power algorithm ‘regular expressions’ to screen
one or multiple viral DNA/RNA sequences in fast format for SSRs and reports
the motif, repeat number, genomic location, abundance of each of six classes
SSRs and many other features useful for SSRs’ studies.

Output:
We have developed a new tool that can be successfully used to identify SSRs in
viral genomes consisting of viral DNA or RNA sequences for escaping
statistical troubles. Judging according to its performance, MfSAT is a definite
advance compared to other available tools. A stand-alone software with several
videos is available online at http://hudacm11.mysinamail.com/hunan.html. This
tool is also available from authors Zhongyang Tan and Guangming Zeng on
request (zhongyang@hnu.cn; zgming@hnu.cn). The output is composed of
three parts: the first part consists of a list of SSRs, each with information such
as repeat motif content, repeat number, starting position, end position, SSR
length; the second part is the numbers of proportions of each of the six classes
of SSRs (mono-, di-, tri-, tetra-, penta- and hexanucleotide repeats); the third
part comprises the numbers of poly(A), poly (T/U), poly(G), poly(C), and 12
classes of dinucleotide repeats including AG, GA, GT (GU), TG (UG), AC,
CA, CT (CU), TC (UC), AT (AU), TA (UA), GC and CG repeats. It is clear
from the results that MfSAT is more attractive in terms of consideration.
Figure 1 shows the software interface and output results of MfSAT.

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BIOINFORMATION

open access
ISSN 0973-2063 (online) 0973-8894 (print)
Bioinformation 6(4): 171-172 (2011)
 

172 © 2011 Biomedical Informatics

Figure 1: Software Interface and Output Results of MfSAT.

Future Work:
Development of a linux version of MfSAT is in process.

Acknowledgments:
The authors sincerely thank Editor and anonymous reviewer for suggestions on
improving the paper. The study was financially supported by Production,
Education and Research guiding
(2010B090400439), Great program for GMO, Ministry of Agriculture of the
people Republic of China (2009ZX08015-003A), the National Natural Science
Foundation of China (No. 50608029, No.50978088, No. 50808073,
No.51039001), Hunan Provincial Innovation Foundation for Postgraduate, the
National Basic Research Program (973 Program) (No. 2005CB724203),
Program for Changjiang Scholars and Innovative Research Team in University

project, Guangdong Province
(IRT0719), the Hunan Provincial Natural Science Foundation of China
(10JJ7005), the Hunan Key Scientific Research Project (2009FJ1010), and
Hunan Provincial Innovation Foundation For Postgraduate (CX2010B157).

References:
[1] Chen M et al. FEBS Lett. 2009 583: 2959 [PMID: 19679131]
[2] Chen M et al. FEBS Lett. 2011 585: 1072 [PMID: 21382371]
[3] Chen M et al. Mol Biol Evol. 2010 27: 2227 [PMID: 20395311]
[4] Usdin K. Genome Res. 2008 18: 1011 [PMID: 18593815]
[5] Li YC et al. Mol Biol Evol. 2004 21: 991 [PMID: 14963101]
[6] Mudunuri SB & Nagarajaram HA. Bioinformatics 2007 23: 1181 [PMID:
17379689]
[7] Mudunuri SB et al. Bioinformation 2010 5: 221 [PMID: 21364802]
Edited by P Kangueane
Citation: Chen et al. Bioinformation 6(4): 171-172 (2011)
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