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BMC Genomics
BioMed Central
Open Access
Database
EuMicroSatdb: A database for microsatellites in the sequenced
genomes of eukaryotes
Veenu Aishwarya1, Atul Grover1,2 and Prakash C Sharma*1
Address: 1University School of Biotechnology, Guru Gobind Singh Indraprastha University, Kashmere Gate, Delhi 110 006, India and 2Shri Radha
Kissen Kanoria Center for Advanced Studies in Bioscience and Biotechnology, Banasthali Vidyapith, Banasthali 304 022 (Raj.) India
Email: Veenu Aishwarya - veenu_aishwarya@yahoo.com; Atul Grover - iatulgrover@gmail.com; Prakash C Sharma* - deansbt@yahoo.co.in
* Corresponding author
Published: 10 July 2007
BMC Genomics 2007, 8:225
doi:10.1186/1471-2164-8-225
Received: 22 November 2006
Accepted: 10 July 2007
This article is available from: http://www.biomedcentral.com/1471-2164/8/225
© 2007 Aishwarya et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Background: Microsatellites have immense utility as molecular markers in different fields like
genome characterization and mapping, phylogeny and evolutionary biology. Existing microsatellite
databases are of limited utility for experimental and computational biologists with regard to their
content and information output. EuMicroSatdb (Eukaryotic MicroSatellite database) http://
ipu.ac.in/usbt/EuMicroSatdb.htm is a web based relational database for easy and efficient positional
mining of microsatellites from sequenced eukaryotic genomes.
Description: A user friendly web interface has been developed for microsatellite data retrieval
using Active Server Pages (ASP). The backend database codes for data extraction and assembly
have been written using Perl based scripts and C++. Precise need based microsatellites data
retrieval is possible using different input parameters like microsatellite type (simple perfect or
compound perfect), repeat unit length (mono- to hexa-nucleotide), repeat number, microsatellite
length and chromosomal location in the genome. Furthermore, information about clustering of
different microsatellites in the genome can also be retrieved. Finally, to facilitate primer designing
for PCR amplification of any desired microsatellite locus, 200 bp upstream and downstream
sequences are provided.
Conclusion: The database allows easy systematic retrieval of comprehensive information about
simple and compound microsatellites, microsatellite clusters and their locus coordinates in 31
sequenced eukaryotic genomes. The information content of the database is useful in different areas
of research like gene tagging, genome mapping, population genetics, germplasm characterization
and in understanding microsatellite dynamics in eukaryotic genomes.
Background
Microsatellites, also called as simple sequence repeats
(SSRs) or simple tandem repeats (STRs) are ubiquitous
component of eukaryotic genomes. A microsatellite consists of a specific sequence of DNA which contains 1–6 bp
long (mono- to hexa- nucleotide) tandem repeats viz.
(A)16, (GA)20, (GATA)30. Over the years, molecular biolo-
gists have increasingly exploited these sequences for
diverse applications.
With the whole genome sequencing initiatives of various
eukaryotic organisms, large amount of genomic sequence
data has accumulated over the last few years. These
sequence resources available in the public domain have
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also served as an attractive source of in silico mining of
microsatellite sequences [1-5]. In silico mining of these
sequences offers advantage in terms of time, labour and
cost over conventional isolation from genomic libraries.
Similarly, ESTs have also been screened for the presence of
microsatellites [6-8]. However, finding potentially useful
microsatellites occupying specific genomic regions still
remains a challenge for the molecular biologists. Availability of this information can facilitate molecular mapping of desired traits and preparation of linkage maps
saturated with evenly distributed SSR markers.
compound) and location (intron, exon, upstream or
transposons) of microsatellites in five insect genomes.
Some other databases [18,19], although published earlier
are currently inaccessible. In conclusion, existing microsatellite databases either are very specific in their content
and application or have limited utility to a wider audience. Thus, a collection of whole genome eukaryotic microsatellite data at a single platform is still not available.
Recognizing this gap, we have developed a comprehensive
database for easy retrieval of information on microsatellites distributed in the sequenced eukaryotic genomes.
The database named as EuMicroSatdb (Eukaryotic MicroSatellite database) presents a web-based user friendly
interface for the extraction of both simple and compound
microsatellites from 31 eukaryotic genomes assembled as
chromosomes. Important features of this database are
compared with those of existing databases in Table 1.
Popularity of in silico mining methods has led to the construction of various microsatellite databases in recent
years, each with a different emphasis. For instance, MICdb
[9] provides information on microsatellites spanning coding and non-coding regions, their frequency, size and
repeat sequence. A recent version of this database covers
19 archeal, 155 eubacterial and 287 viral genomes. SilkSatDb [10] incorporates microsatellites extracted from the
available ESTs and genomic sequences of the silkmoth
(Bombyx mori). This database also stores data on polymorphism status of different microsatellite loci. Similarly,
mouse genomic microsatellites are collected in the Mouse
Microsatellite Database of Japan (MMDBJ) [11]. CMD
(Cotton Microsatellite Database) is a web-based relational
database providing centralized access to publicly available
cotton microsatellites. The database also provides a useful
resource for mapping and related data pertaining to major
cotton microsatellite projects [12]. Satellog [13] database
catalogues triplet repeats associated with human disorders. Similarly Microsat2006 [14] database catalogues
human microsatellite repeats. Taiwanese Polymorphic
Microsatellite Database (TPMD) provides data on microsatellite mapping in the Taiwanese populations [15].
Molecular Mycology Research Laboratory, Westmead,
Australia has created an SSR database [16] that stores
information on microsatellite repeats in nine fungal
genomes. InSatDb [17] provides size, type (perfect and
Construction and Content
EuMicroSatdb is a platform independent relational database. The basic scheme followed for the development of
EuMicroSatdb involved following steps: (1) whole
genome sequences were downloaded from various
sources like Ensembl [20], The National Center for Biotechnology Information (NCBI) [21], Genolevures 2 [22],
International Rice Genome Sequencing Project (IRGSP)
[23], Beijing Genomics Institute (BGI) [24], The Arabidopsis Information Resource (TAIR) [25] (Table 2) and
scanned using a simple sequence repeat mining tool
called MISA [26]; (2) filtering and restructuring of the
required data using novel algorithms, VRFINE (creates
"rfine" file that has sequence information of microsatellites) and VRSTRUCT (uses "rfine" file and processes it to
make three separate files for repeat number, repeat motif
and repeat unit length); (3) extraction of 200 bp upstream
and downstream flanking sequences using a C++ program
called VEXTRACT that creates two separate files, one each
for upstream and downstream sequences; (4) microsatellite clustering information was generated using a Perl
Table 1: Comparison of various microsatellite databases, available in the public domain
Database
Details on
Coverage
Simple
Repeats
Compound
Repeats
Clustering
information
Genomic
Positions
Flanking
Sequences
MICdb [9]
Y
Y
N
Y
Y
SilkSatDb [10]
MMDBJ [11]
CMD [12]
Satellog [13]
Database of Molecular Mycology
Research Lab. [16]
InSatDb [17]
MRD [18]
SSRD [19]
EuMicroSatdb
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
N
N
N
N
Y
Y
Y
N
Y
N
N
19 archeal, 155 bacterial and
287 viral genomes
Silkworm
Mouse
Cotton
Human
9 fungal genomes
Y
Y
Y
Y
Y
N
N
Y
N
N
N
Y
Y
N
N
Y
Y
N
N
Y
5 insect genomes
8 eukaryotic genomes
Human
31 eukaryotic genomes
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Table 2: Details of genomes included in EuMicroSatdb
Species
Saccharomyces cerevisiae
Schizosaccharomyces pombe
Aspergillus oryzae RIB40
Aspergillus fumigatus
Cryptococcus neoformans varJEC21
Encephalitozoon cuniculi
Eremothecium gossypii
Candida glabrata CBS138
Debaryomyces hansenii
Kluyveromyces lactis
Yarrowia lipolytica
Caenorhabditis elegans
Plasmodium falciparum
Anopheles gambiae
Drosophila melanogaster
Apis mellifera
Tribolium castaneum
Oryza sativa ssp.japonica
Oryza sativa ssp. indica
Arabidopsis thaliana
Ciona intestinalis
Tetraodon nigroviridis
Danio rerio
Rattus norvegicus
Mus musculus
Gallus gallus
Canis familiaris
Macaca mulatta
Bos taurus
Pan troglodytes
Homo sapiens
Build/Assembly/Ver.
Source
Web Link
SGD 1, Nov 2005
NCBI release
NCBI release
NCBI release
NCBI release
NCBI release
NCBI release
Genolevures 2 Release 2, May 2006
Genolevures 2 Release 2, May 2006
Genolevures 2 Release 2, May 2006
Genolevures 2 Release 2, May 2006
WS160, July 2006
NCBI release
AgamP3, Feb 2006
BDGP 4.3, July 2005
NCBI release
NCBI release
Build 4.0
2003-08-01 BGI
ver. Jan 22 2004
JGI 2, Mar 2005
TETRAODON 7, Apr 2003
Zv6, Mar 2006
RGSC 3.4, Dec 2004
NCBI m36, Dec 2005
WASHU2, May 2006
CanFam 1.0, July 2004
MMUL 1.0, Feb 2006
Btau_3.1, Aug 2006
PanTro 2.1, Mar 2006
NCBI 36, Oct 2005
Ensembl
NCBI
NCBI
NCBI
NCBI
NCBI
NCBI
Genolevures
Genolevures
Genolevures
Genolevures
Ensembl
NCBI
Ensembl
Ensembl
NCBI
NCBI
IRGSP
BGI
TAIR
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
Ensembl
http://www.ensembl.org
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
http://cbi.labri.u-bordeaux.fr
http://cbi.labri.u-bordeaux.fr
http://cbi.labri.u-bordeaux.fr
http://cbi.labri.u-bordeaux.fr
http://www.ensembl.org
ftp://ftp.ncbi.nlm.nih.gov
http://www.ensembl.org
http://www.ensembl.org
ftp://ftp.ncbi.nlm.nih.gov
ftp://ftp.ncbi.nlm.nih.gov
http://rgp.dna.affrc.go.jp/IRGSP/
http://rise.genomics.org.cn
http://www.arabidopsis.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
http://www.ensembl.org
based script VCLUST, and (5) all the data generated by
above algorithms were reassembled into a data file using
another Perl based script VDATA_ASSEMBL. This file was
then imported in MS-ACCESS as a table. The overall
scheme of database construction is explained in figure 1.
Sub-databases were constructed for individual genomes
by importing all data files as tables, each representing one
chromosome. Finally, an Index-database was created that
communicates with these sub-databases. Front end web
interface was developed using ASP that communicates
with the Index database for data retrieval. The overall
architecture of the database is outlined in figure 2.
Utility and Discussion
The EuMicroSatdb allows mining of different microsatellites along with their physical location on chromosomes
in completely/almost completely sequenced eukaryotic
genomes. At present, the database has over 10 million
entries of microsatellites covering 31 genomes (Table 2).
More genomes will be included in the database as and
when their whole genome sequences are published and
made available in the public domain.
User can search for perfect repeats, compound (perfect)
repeats and microsatellite clusters. EuMicroSatdb database
can be searched using following need based input parameters: Repeat unit length: the basic unit that is tandemly
repeated in the microsatellite ranging from mononucleotide to hexanucleotide; Repeat sequence: this parameter
allows the user to search microsatellite for a specific base
sequence, for example, AT, GCG, etc.; Repeat number: is
used to search microsatellites on the basis of repeat
number of the microsatellite e.g. (CCT)9 has a repeat
number of 9, (AGAGG)10 has a repeat number of 10; Microsatellite length: searches microsatellites on the basis of
their total length in base pairs e.g. (TTGCA)5 has a length
of 25 bp; Position: defined locations on the chromosome
in terms of base pairs can be specified; Microsatellite cluster: search can also be performed to look for adjacent microsatellites. Further, if the user wants to design primers for
PCR amplification of the desired microsatellite locus, the
database also provides 200 bp upstream and downstream
regions of all the microsatellite loci. The search options
are further explained with the help of some case studies
given in a power point tutorial available on the database
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Figure 1
Construction scheme of EuMicroSatdb
Construction scheme of EuMicroSatdb. Figure describing methodology used for preparation of backend (codes used in
the preparation of files in the database) and front end (the web interface of the database).
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Figure 2
Architecture of EuMicroSatdb
Architecture of EuMicroSatdb. Scheme of EuMicroSatdb describing the outline of the database.
website. Figure 3 displays the user interface for searching
microsatellites by using one or more of the above-mentioned basic parameters.
The unique feature of this database is the extraction of
both simple and compound microsatellites. Compound
repeats can be searched by specifying motifs desired in the
combination. For example, if a user wants to search for a
compound microsatellite from chromosome 1 of Homo
sapiens which is more than 100 bp in length, has a TTTCTC-TTTC repeat combination with the fourth association
being a dinucleotide repeat, with repeat number greater
than 10 for TTTC and TC, search can be made by using the
parameters specified in figure 4A. The output of this query
is shown in figure 4B.
User can identify the genomic regions showing high microsatellite density to study microsatellite clustering in the
genome [27] by defining the size of interruption between
neighbouring microsatellites as explained in the database
tutorial.
EuMicroSatdb is likely to be adopted as a useful tool to
study the relative occurrence and distribution of microsatellites across eukaryotic genomes. The information may
have diverse applications. The user can extract the position of the microsatellite on the chromosome and thus
can link it with the gene co-ordinates, which are available
on various public domains. In this way, microsatellites
located in the vicinity of genes may be identified. These
microsatellites will hopefully prove to be more useful for
gene tagging and to investigate the role of microsatellites
in gene regulation. Similarly, microsatellites spanning
desired genomic regions can be selected and used for further saturation of existing molecular maps. Since microsatellite show varying levels of cross amplification among
related genomes, microsatellites from the genomes
included in the present database can be exploited for
developing markers in the related species where sufficient
STMS markers are still not available. The compound microsatellites being hypervariable can prove to be a potential
source of highly polymorphic markers.
Incorporation of multiple sub-databases in EuMicroSatdb
ensures faster exchange of information and unlimited
expansion of the database. The database will be upgraded
regularly as and when draft assemblies are updated and
new genomes are sequenced. EuMicroSatdb is compatible
with multi-user environment. The efficiency of data
retrieval is maintained during simultaneous access by
many users.
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Figure 3
Web interface for simple microsatellite searching
Web interface for simple microsatellite searching. Web interface showing (A) various input parameters used for simple
microsatellite based search, (B) output of the query, and (C) 200 bp upstream/downstream sequences for a particular microsatellite.
Conclusion
EuMicrosatdb has been developed for genome wide mining of microsatellite in 31 completely sequenced eukaryotic genomes considering the immense utility of these
sequences for a variety of experiments. Various parameters
have been carefully inducted to allow comprehensive
search of simple and compound microsatellites and to
identify microsatellite clusters across the genomes. Links
to retrieve flanking sequences (200 bp upstream and
downstream) are provided to design primers for PCR
amplification of desired motifs. EuMicroSatdb will provide a useful resource for mining microsatellites to be
used in gene tagging, comparative genomics and genetic
diversity based studies in different genomes
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Figure 4
Web interface for searching compound microsatellite
Web interface for searching compound microsatellite. Web interface showing (A) various input parameters used for
searching compound microsatellite, and (B) output of the query.
Availability and requirements
EuMicroSatdb is a platform independent relational database publicly available at http://ipu.ac.in/usbt/EuMicro
Satdb.htm
sity School of Information Technology, Guru Gobind Singh Indraprastha
University, Delhi.
References
1.
Authors' contributions
VA was mainly responsible for writing codes, designing
the architecture of the database and execution of the
study. AG participated in designing of the database and
helped in the preparation of the manuscript. PCS conceived, coordinated and supervised the study. All authors
read and approved the final manuscript.
2.
3.
4.
Acknowledgements
The EuMicroSatdb team would like to thank Prof. K.K. Aggarwal, Vice-chancellor Guru Gobind Singh Indraprastha University, Delhi for encouragement and constructive suggestions throughout the project. We also
acknowledge the technical support received from Mr. Ajeet Pratap, Univer-
5.
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