Skip to main content

FishMicrosat: a microsatellite database of commercially important fishes and shellfishes of the Indian subcontinent

Abstract

Background

Microsatellite DNA is one of many powerful genetic markers used for the construction of genetic linkage maps and the study of population genetics. The biological databases in public domain hold vast numbers of microsatellite sequences for many organisms including fishes. The microsatellite data available in these data sources were extracted and managed into a database that facilitates sequences analysis and browsing relevant information. The system also helps to design primer sequences for flanking regions of repeat loci for PCR identification of polymorphism within populations.

Description

FishMicrosat is a database of microsatellite sequences of fishes and shellfishes that includes important aquaculture species such as Lates calcarifer, Ctenopharyngodon idella, Hypophthalmichthys molitrix, Penaeus monodon, Labeo rohita, Oreochromis niloticus, Fenneropenaeus indicus and Macrobrachium rosenbergii. The database contains 4398 microsatellite sequences of 41 species belonging to 15 families from the Indian subcontinent. GenBank of NCBI was used as a prime data source for developing the database. The database presents information about simple and compound microsatellites, their clusters and locus orientation within sequences. The database has been integrated with different tools in a web interface such as primer designing, locus finding, mapping repeats, detecting similarities among sequences across species, and searching using motifs and keywords. In addition, the database has the ability to browse information on the top 10 families and the top 10 species, through record overview.

Conclusions

FishMicrosat database is a useful resource for fish and shellfish microsatellite analyses and locus identification across species, which has important applications in population genetics, evolutionary studies and genetic relatedness among species. The database can be expanded further to include the microsatellite data of fishes and shellfishes from other regions and available information on genome sequencing project of species of aquaculture importance.

Background

Microsatellites are observed in almost all known eukaryotic and prokaryotic genomes, present in both coding and non-coding regions. They have a high mutation rate (between 10-3 and 10-4 mutations per gamete per generation) that generates and maintains extensive length polymorphism[1, 2]. This makes microsatellite a powerful genetic marker for a variety of applications like population genetics, genetic linkage mapping, parentage assignment, marker assisted selection, molecular breeding, and allele mining[3, 4]. A microsatellite locus generally varies in length between 5 to 40 repeats. Di-, tri- and tetranucleotide repeats are the most common choices for molecular genetic studies. Dinucleotides are an abundant type of microsatellite repeat found in most vertebrates, whereas trinucleotide repeats are most abundant in plants[5–7]. Microsatellites represent ideal molecular markers because they have multiple alleles that are highly polymorphic among individuals and loci that are highly abundant and dispersed evenly throughout eukaryotic genomes. The major drawback of using microsatellite is that for most species they need to be developed de novo, a process that is often costly and protracted[8]. Efforts have been made worldwide to compile and develop online and offline microsatellite databases of biological organisms[9–15]. Valuable studies have been done in fishes such as microsatellite genetic linkage maps[16–20], characterization and identification of microsatellites[21–24] and cross-species microsatellite locus identification[25–27]. Despite the importance of microsatellite markers, meagre efforts have been made to develop a microsatellite database of the fishes except Danio rerio[28], Cyprinus carpio[29] and Fishgen[30].

In this article, we describe the development of a microsatellite database (FishMicrosat) for population genetics and stock management using LAMPP (Linux-Apache-MySQL-PHP-Perl) technology and GenBank of NCBI as a data source to extract the microsatellite data. FishMicrosat is a unique database of microsatellite sequences that covers commercially important fish and shellfish species of the Indian subcontinent. The database currently contains 4398 sequences of 41 species belonging to 15 families and provides information on the type of repeat in terms of mono-, di-, tri-, tetra-, penta and hexanucleotide, simple and compound microsatellite, along with the characteristic of repeats namely size, region, pattern & unit. Additionally, algorithms were implemented for finding loci across species, based on the presence of identical simple sequence repeats (SSRs) with the same or varying frequencies of repeat units but conserved flanking regions. The database is regularly updated based on the release of new records in GenBank for the existing 41 species as well as the addition of new species belonging to the Indian sub continent. It is expected that the database will be a valuable resource in many aspects of fish genetic research of the Indo-Pacific region, Bay of Bengal and Arabian Sea.

Construction and content

Data source

Microsatellite sequences of fish and shellfish species were downloaded from Entrez of NCBI[31] using the keyword search ‘Fish microsatellite’ under nucleotide. Files were downloaded in GenBank and FASTA format for annotation and sequences respectively. Further, a Perl program (SpciesExtractor.pl) was written and used for data extraction for only important species found in the Indian subcontinent from the downloaded files. Other physical information about the species like habitat, distribution, IUCN Red List status was collected from FishBase[32]. Another Perl parsing program (InformationParser.pl) was developed to extract the information from the files according to the database schema and manage the data into the database. These Perl programs are used by the database administrator for updating based on new releases of microsatellite sequences for existing and new species.

Design and development

Database

In order to manage the data, MySQL, a relational database management system, was used for building the database. Tables were designed and relationships among tables were created using unique, primary and foreign keys. Five tables were designed to store the information about microsatellite sequences and species. Table ‘fishinfo’ contains the physical and phenotypical information; ‘satellite_sources’ holds details molecular information about microsatellites; ‘satellite’ works as a bridge between tables ‘fishinfo’ and ‘satellite_sources’; ‘taxonomy’ shows systematic information of the species and acts as a sub table of ‘fishinfo’. And finally the table ‘repeats’ covers the data about repeats of all microsatellites sequences obtained by using the repeat analysis program ‘MISA’[33] as shown in Figure 1.

Figure 1
figure 1

Architecture and data flow representation in ‘FishMicrosat’.

Web interface

A web interface integrated with the database was designed and developed to retrieve and access the information of interest using web technologies like PHP, HTML, CSS, JavaScripts, DBI (Database Interface), CGI (Common Gateway Interface), GD (Graphic Design) and Perl. The web interface also incorporates the different tools for searching, viewing and analysing the microsatellite data (Figure 1).

Identification of microsatellite loci across species

The microsatellite loci among the existing sequences were identified by implementing an algorithm into a program (locusfinder.pl) using Perl. In order to construct the algorithm, a microsatellite sequence of selected species was divided in parts (a) motif of repeats region (b) 25 bp flanking sequence upstream and (c) 25 bp flanking sequence downstream to the repeat region. The repeat region and motifs present in sequences of selected species were fetched from the ‘repeats’ table of the database sequentially for retrieving identical target motifs and its sequences. Further, the conserved flanking regions were checked in query as well as target sequences. The evolutionary conservation of the flanking region allows hetero specific identification of SSRs[34]. These conserved flanking regions have been used for designing PCR primers for microsatellite amplification and genotyping of individuals of the same species as well as across species[35, 36]. Thus, to identify loci across species, an algorithm was designed by considering the approach for example ‘ABC’ as a repeat pattern and ‘L’ the number of repeat units in a selected query sequence. The same repeat pattern ‘ABC’ was used to check its availability and repeat frequency (denoted as P) in the target sequence (Figure 2). Here, because the repeat frequency may be polymorphic, the value of the repeat frequency in the selected query sequence (L) may or may not be equal to the repeat frequency in the target sequence (P) i.e. L = P or L! = P. The algorithm uses a 25 bp length of flanking region on either side, which is sufficient for amplification of a microsatellite locus in a PCR reaction for laboratory validation. The loci identification program supports the findings of the previous studies that microsatellite repeats vary within and between different genomes of organisms[37, 38].

Figure 2
figure 2

Flowchart of the locus finder algorithm.

Search and analysis

Apart from locus finding across species, other search and analysis modules like ‘Keyword search’, ‘Repeat analysis and primer’, ‘Motifs search’, and ‘Repeats map’ were implemented and integrated in the web interface for browsing information. The ‘Keyword search’ takes a word like ‘fish name’, ‘common name’, ‘family’, ‘accession number’ and ‘author’ typed in by the user as input and performs the search. The ‘Motif search’ takes input parameters like motifs, repeat length and repeat type (simple or composite) and returns the result with the help of regular expression programming and SQL (Structured Query Language) concepts. The ‘Repeats map’ was developed using Perl, MISA and Blastn[39] programs for identifying similarities among the sequences and mapping the repeats. The Blastn program uses ‘blastmsdb’ database, which is a blast compatible and created apart from the main database by using ‘formatdb’ program of blast package. ‘Repeats map’ analyzes and process the input query sequence through the MISA program to generate the repeats. If repeats are found, it further leads to alignment with other similar sequences; otherwise the program terminates with a warning message. Primer3 program[40, 41] was used for primer designing, and a standalone version was downloaded[42] to compute multiple sets of forward and reverse primers for microsatellite loci along with melting temperature (Tm), GC content, start position and product size. These generated primers can be used in PCR reactions for identification of polymorphic loci for genotyping of individuals.

Implementation of ‘statistics’

The MISA program was implemented to ascertain the frequently occurring repeat types and repeat information from all the sequences in FishMicrosat. The results obtained from MISA were parsed and stored in the ‘repeats’ table of the database. The ‘GD graph’ module was used to design and dynamically display the frequency of different types of repeats (mono to hexa) in the ‘Pie diagram’. The ‘Pie diagram’ presents the frequency of each type of repeat and is revised when the database is updated.

Discussion and utility

FishMicrosat covers 4398 microsatellite records of 41 commercially important aquaculture species belonging to 15 families (Table 1). The Home page of the web interface of FishMicrosat integrated with different analytical modules, presents the numerical statistics of the top 10 families and species in addition to providing information on updating and current status of the database. The ‘Top 10 FishMicrosat families’ displays ten families which has the largest number of species in FishMicrosat and the ‘Top 10 FishMicrosat Species’ displays the ten species for which the largest number of specimen records are available in the database. The page also provides an overview of FishMicrosat and its features. The analytical tools like motif, sequence similarity search and repeat mapping, and finding microsatellite loci across species were integrated to increase the utility and scope of the database.

Table 1 Distribution of SSR’s by species

Browsing specimen information

The specimen records of the species of interest can be viewed by using the species instantiation index under the ‘Record overview’ menu item in the web interface. Hyperlinked navigational indexes by first letter of the generic name have been provided to find the species of interest along with the number of specimen records in square brackets. Further, selection of each species name is hyperlinked and a mouse click over the species name presents information on family, common name, habitat, distribution, microsatellite repeats, its region and size, sequence length, authors and NCBI accession number. The NCBI accession number for each specimen record also has a hyperlink to NCBI. The ‘Top 10 FishMicrosat families’ and ‘Top 10 FishMicrosat Species’ on the home page of the web interface provides other means of viewing information about the species and its specimens.

Keyword search

The keyword search works on keywords like species name, common name, family name, accession number, and author for retrieving the information from the database. Different views have been created for all these keywords to present relevant information from the database. For example the species name or common name as an input keyword leads to record overview. The ‘author view’ displays a list of all the species on which the particular author worked and also displays the specimen records which corresponds to the listed species. Similarly, family name and accession number keywords also lead to respective views (Figure 3).

Figure 3
figure 3

Search results for different keywords in ‘FishMicrosat’.

Repeat analysis and primer design

The menu item ‘Analysis & primer’ (Figure 4A) detects repeats in the sequences and designs the primer for the selected repeat locus. Thus, to obtain the repeat information and design primers for a specific repeat, the end user selects a species of interest starting with a generic name. Clicking on the species name provides a table that contains information such as accession no., SSR no., SSR type, SSR motif, SSR size, position, sequence length and a link for primer design for each specimen (Figure 4B). For primer designing, the ‘Primer3’ standalone program computes primers upon user request for microsatellite sequences that have suitable length of flanking regions and ample GC content in that region; otherwise the request is rejected with a warning message (Figure 4C). The program displays a list of multiple primers along with respective values for Tm, GC content, start position and product size (oligo size). The primer sequences will be useful in determining the alleles and finding of loci across species.

Figure 4
figure 4

The web layout for SSR analysis and primer design of ‘FishMicrosat’. (A) Species specific SSR analysis and primer design (B) repeat analysis output (C) SSR specific primer design output.

Motif search

A repeat motif can be searched from the menu item ‘Motif search’ integrated in the web interface (Figure 5A). It searches repeats in all microsatellite sequences present in the database and fetches information on species name, family, repeats, size, repeat region, NCBI references, and primers for SSRs (Figure 5B). Three input values are required under ‘Motif search’: ‘Motif’ for nucleotide pattern (mono-hexa), ‘Length’ for number of nucleotides (i.e. > 10) and ‘Repeats type’ (simple or compound). The search results provide a primer link that leads to the design of the primer for the corresponding repeat type.

Figure 5
figure 5

The different web layouts of ‘FishMicrosat’ for data retrieval and analyses. (A) Home page (B) Motif search (C) Locus finder (D) Repeats map (E) Repeats statistics.

Locus finder

The Locus finder tab accesses identical microsatellite loci across species based on conserved flanking sequences (approximately 25 bp long) on either side of the polymorphic loci. The program uses two input parameters; length of flanking region and species name. Finding the identical microsatellite locus in other species existing in the FishMicrosat database, is highly useful for cross species amplification of microsatellite loci. For example the sequence of Labeo rohita (GenBank accession no. AY291597) and Catla catla (GenBank accession no. AJ294957) contain the same motif with conserved flanking regions on the parameter: flanking region ‘20 bp’ and species ‘Labeo rohita’. The sequence alignments are 88% identitical, indicating homology between sequences (Figure 5C).

Repeats map

Repeat mapping and sequence similarity searching can be achieved through the menu item ‘Repeats map’ included in the web interface. The program accepts microsatellite sequences in FASTA format as input in the provided text area. The output presents information on repeats (size of query sequence, presence of compound/composite repeats, number of identified repeats in query sequence SSRs, SSRs number, repeats location and size of repeats) along with summary on alignment of identical/similar sequences. The alignment summary presents targeted sequences accession no., species name, target length, gaps, matches and identity between query and targeted sequences (Figure 5D). The program initially checks the presence or absence of the repeats in the input sequence and assigns a boolean value. If the value is true the program processes the query sequences by using Blastn program and its compatible ‘blastmsdb’ database for similar sequence searches. Thus, it helps to find information about repeats orientation and sequence similarity for the newly generated microsatellite sequences.

Repeat statistics

In order to determine the frequency of different types of repeats from the specimen records available in FishMicrosat, the menu item ‘Statistics’ generates the frequency of each motif found in the database and displays the top three (most common) motifs with the largest frequencies. For example, the statistic view shows that repeats ‘AC’ was found 998 times, ‘TG’ 909 and ‘CA’ 881 throughout all sequences. A repeat type index has also been included to display all the repeats and their frequencies in a table. The dinucleotide repeat type selected as default displays 12 combinations of dinucleotides. The maximum frequency of each type of nucleotide repeats (mono to hexa) can be viewed in the pie diagram (Figure 5E). The largest frequency for a mononucleotide repeat is ‘T’ with 129 occurrences, dinucleotide repeats ‘AC’ with 998 occurrences, trinucleotide repeats ‘CAT’ with 48 occurrences, tetranucleotide ‘ATCT’ with 56 occurrences, pentanucleotide ‘TTATC’ with 2 occurrences and hexanucleotide ‘CACACT’ with 4 occurrences. The database with 4398 sequences of 41 species has 277 mono, 4207 di, 610 tri, 554 tetra, 15 penta, 11 hexa and 279 compound repeats (Table 1). This section also analyzes information on the occurrence of the most frequent and rare nucleotide repeats in the fish genome. The dinucleotide repeats AC|TG (998|909) and CA|GT (881|686) were frequently found while CG|GC (9|7) were rare in fish genome.

Conclusions

FishMicrosat is a database of microsatellite sequences of commercially important fishes including shrimps and currently covers 4398 specimen records for 41 species. The database facilitates mining of SSR motifs, repeat orientations and sequence similarities. The statistics presents the relative abundance of microsatellite repeats that occur frequently in the genomes. Additionally, it facilitates in identifying polymorphic loci across species and designing primers for repeat loci, thus providing researchers ready to use information from a centralized location, avoiding the cumbersome process of referring to multiple sources of literature and using multiple programmes. This repository with included tools can play a key role in cutting edge areas of research by assisting with marker selection, linkage mapping, population genetics, evolutionary studies, genetic relatedness among the species and genetic improvement programmes of important aquaculture species.

Availability and requirement

FishMicrosat is freely accessible at URL http://mail.nbfgr.res.in/fishmicrosat/ for research and academic use.

References

  1. Weber JL, Wong C: Mutation of human short tandem repeats. Hum Mol Genet. 1993, 2: 1123-1128. 10.1093/hmg/2.8.1123.

    Article  CAS  PubMed  Google Scholar 

  2. Tautz D, Renz M: Simple sequences are ubiquitous repetitive components of eukaryotic genomes. Nucleic Acids Res. 1984, 12: 4127-4138. 10.1093/nar/12.10.4127.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. Jarne P, Lagoda PJ: Microsatellites, from molecules to populations and back. Trends Ecol Evol. 1996, 11: 424-429. 10.1016/0169-5347(96)10049-5.

    Article  CAS  PubMed  Google Scholar 

  4. Bruford MW, Wayne RK: Microsatellites and their application to population genetic studies. Curr Opin Genet Dev. 1993, 3: 939-943. 10.1016/0959-437X(93)90017-J.

    Article  CAS  PubMed  Google Scholar 

  5. Beckmann JS, Weber JL: Survey of human and rat microsatellites. Genomics. 1992, 12: 627-631. 10.1016/0888-7543(92)90285-Z.

    Article  CAS  Google Scholar 

  6. Chen C, Zhou P, Choi YA, Huang S, Gmitter FG: Mining and characterizing microsatellites from citrus ESTs. Theor Appl Genet. 2006, 112: 1248-1257. 10.1007/s00122-006-0226-1.

    Article  CAS  PubMed  Google Scholar 

  7. Kantety RV, La Rota M, Matthews DE, Sorrells ME: Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat. Plant Mol Biol. 2002, 48: 501-510. 10.1023/A:1014875206165.

    Article  CAS  PubMed  Google Scholar 

  8. Zane L, Bargelloni L, Patarnello T: Strategies for microsatellite isolation: a review. Mol Ecol. 2002, 11: 1-16. 10.1046/j.0962-1083.2001.01418.x.

    Article  CAS  PubMed  Google Scholar 

  9. Sakai T, Miura I, Yamada-Ishibashi S, Wakita Y, Kohara Y, Yamazaki Y, Inoue T, Kominami R, Moriwaki K, Shiroishi T, Yonekawa H, Kikkawa Y: Update of mouse microsatellite database of Japan (MMDBJ). Exp Anim. 2004, 53: 151-154. 10.1538/expanim.53.151.

    Article  CAS  PubMed  Google Scholar 

  10. Subramanian S, Madgula VM, George R, Kumar S, Pandit MW, Singh L: SSRD: simple sequence repeats database of the human genome. Comp Funct Genomics. 2003, 4: 342-345. 10.1002/cfg.289.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Missirlis PI, Mead CL, Butland SL, Ouellette BF, Devon RS, Leavitt BR, Holt RA: Satellog: a database for the identification and prioritization of satellite repeats in disease association Studies. BMC Bioinforma. 2005, 6: 145-10.1186/1471-2105-6-145.

    Article  Google Scholar 

  12. Aishwarya V, Grover A, Sharma PC: EuMicroSatdb: a database for microsatellites in the sequenced genomes of eukaryotes. BMC Genomics. 2007, 8: 225-10.1186/1471-2164-8-225.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Boby T, Patch AM, Aves SJ: TRbase: a database relating tandem repeats to disease genes for the human genome. Bioinformatics. 2005, 21: 811-816. 10.1093/bioinformatics/bti059.

    Article  CAS  PubMed  Google Scholar 

  14. Archak S, Meduri E, Kumar PS, Nagaraju J: InSatDb: a microsatellite database of fully sequenced insect genomes. Nucleic Acids Res. 2007, 35: D36-D39. 10.1093/nar/gkl778.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Gelfand Y, Rodriguez A, Benson G: TRDB: the tandem repeats database. Nucleic Acids Res. 2007, 35: D80-D87. 10.1093/nar/gkl1013.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Knapik EW, Goodman A, Ekker M, Chevrette M, Delgado J, Neuhauss S, Shimoda N, Driever W, Fishman MC, Jacob HJ: A microsatellite genetic linkage map for zebrafish (Danio rerio). Nat Genet. 1998, 18: 338-343. 10.1038/ng0498-338.

    Article  CAS  PubMed  Google Scholar 

  17. Ardren WR, Borer S, Thrower F, Joyce JE, Kapuscinski AR: Inheritance of 12 microsatellite loci in Oncorhynchus mykiss. J Hered. 1999, 90: 529-536. 10.1093/jhered/90.5.529.

    Article  CAS  Google Scholar 

  18. Gilbey J, Verspoor E, McLay A, Houlihan D: A microsatellite linkage map for Atlantic salmon (Salmo salar). Anim Genet. 2004, 35: 98-105. 10.1111/j.1365-2052.2004.01091.x.

    Article  CAS  PubMed  Google Scholar 

  19. Liu S, Rexroad CE, Couch CR, Cordes JF, Reece KS, Sullivan CV: A microsatellite linkage map of striped bass (Morone saxatilis) reveals conserved synteny with the three-spined stickleback (Gasterosteus aculeatus). Mar Biotechnol. 2012, 14: 237-244. 10.1007/s10126-011-9407-2.

    Article  CAS  PubMed  Google Scholar 

  20. Liu F, Sun F, Li J, Xia JH, Lin G, Tu RJ, Yue GH: A microsatellite-based linkage map of salt tolerant tilapia (Oreochromis mossambicus × Oreochromis spp.) and mapping of sex-determining loci. BMC Genomics. 2013, 14: 58-62. 10.1186/1471-2164-14-58.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Abdul Rahman Z, Choay-Hoong L, Mat Khairuddin R, Ab Razak S, Othman AS: Isolation and characterization of novel microsatellite loci for Asian sea bass, Lates calcarifer from genome sequence survey database. J Genet. 2012, 91: e82-e85.

    PubMed  Google Scholar 

  22. Nikolic N, Fève K, Chevalet C, Høyheim B, Riquet J: A set of 37 microsatellite DNA markers for genetic diversity and structure analysis of Atlantic salmon Salmo salar populations. J Fish Biol. 2009, 74: 458-466. 10.1111/j.1095-8649.2008.02094.x.

    Article  CAS  PubMed  Google Scholar 

  23. Sha Z, Wang S, Zhuang Z, Wang Q, Wang Q, Li P, Ding H, Wang N, Liu Z, Chen S: Generation and analysis of 10 000 ESTs from the half-smooth tongue sole Cynoglossus semilaevis and identification of microsatellite and SNP markers. J Fish Biol. 2010, 76: 1190-1204. 10.1111/j.1095-8649.2010.02592.x.

    Article  CAS  PubMed  Google Scholar 

  24. Patel A, Das P, Swain SK, Meher PK, Jayasankar P, Sarangi N: Development of 21 new microsatellite markers in Labeo rohita (rohu). Anim Genet. 2009, 40: 253-254. 10.1111/j.1365-2052.2008.01834.x.

    Article  CAS  PubMed  Google Scholar 

  25. Mendonça FF, Ussami LH, Hashimoto DT, Pereira LH, Porto-Foresti F, Oliveira C, Gadig OB, Foresti F: Identification and characterization of polymorphic microsatellite loci in the blue shark Prionace glauca, and cross-amplification in other shark species. J Fish Biol. 2012, 80: 2643-2646. 10.1111/j.1095-8649.2012.03291.x.

    Article  PubMed  Google Scholar 

  26. Tong J, Wang Z, Yu X, Wu Q, Chu KH: Cross-species amplification in silver carp and bighead carp with microsatellite primers of common carp. Mol Ecol Notes. 2002, 2: 245-247. 10.1046/j.1471-8286.2002.00214.x.

    Article  CAS  Google Scholar 

  27. Liao M, Yang G, Wang X, Wang D, Zou G, Wei Q: Development of microsatellite DNA markers of silver carp (Hypophthalmichthys molitrix) and their cross-species application in bighead carp (Aristichthys nobilis). Mol Ecol Notes. 2007, 7: 95-99.

    Article  CAS  Google Scholar 

  28. Rouchka EC: Database of exact tandem repeats in the Zebrafish genome. BMC Genomics. 2010, 11: 347-10.1186/1471-2164-11-347.

    Article  PubMed Central  PubMed  Google Scholar 

  29. Mao RX, Liu FJ, Zhang XF, Zhang Y, Cao DC, Lu CY, Liang LQ, Sun XW: Studies on quantitative trait loci related to activity of lactate dehydrogenase in common carp (Cyprinus carpio). Yi Chuan. 2009, 31: 407-411. 10.3724/SP.J.1005.2009.00407.

    Article  CAS  PubMed  Google Scholar 

  30. Imsiridou A, Hardy H, Maudling N, Amoutzias G, Zaldívar Comenges JM: Web database of molecular genetic data from fish stocks. J Hered. 2003, 94: 265-267. 10.1093/jhered/esg057.

    Article  CAS  PubMed  Google Scholar 

  31. Benson DA, Karsch-Mizrachi I, Clark K, Lipman DJ, Ostell J, Sayers EW: GenBank. Nucleic Acids Res. 2012, 40: D48-D53. 10.1093/nar/gkr1202.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  32. FishBase database.http://www.fishbase.org,

  33. MISA source program.http://pgrc.ipk-gatersleben.de/misa/,

  34. Estoup A, Angers B: Microsatellites and minisatellites for molecular ecology: theoretical and empirical considerations. Advances in Molecular Ecology. Edited by: Carvalho GR. 1998, IOS press, Ohmsha; Nato Sience Series, 55-79. 2

    Google Scholar 

  35. Rico C, Rico I, Hewitt G: 470 million years of conservation of microsatellite loci among fish species. Proc Biol Sci. 1996, 263: 549-557. 10.1098/rspb.1996.0083.

    Article  CAS  PubMed  Google Scholar 

  36. Primmer CR, Møller AP, Ellegren H: A wide-range survey of cross-species microsatellite amplification in birds. Mol Ecol. 1996, 5: 365-378.

    Article  CAS  PubMed  Google Scholar 

  37. Kong J, Gao H: Analysis of tandem repeats in the genome of Chinese shrimp Fenneropenaeus chinensis. Chin Sci Bull. 2005, 50: 1462-1469. 10.1360/982005-270.

    Article  CAS  Google Scholar 

  38. Katti MV, Ranjekar PK, Gupta VS: Differential distribution of simple sequence repeats in eukaryotic genome sequences. Mol Biol Evol. 2001, 18: 1161-1167. 10.1093/oxfordjournals.molbev.a003903.

    Article  CAS  PubMed  Google Scholar 

  39. Altschul SF, Gish W, Miller W: Basic local alignment search tool. J Mol Biol. 1990, 215: 403-410.

    Article  CAS  PubMed  Google Scholar 

  40. Rozen S, Skaletsky H: Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol. 2000, 132: 365-386.

    CAS  PubMed  Google Scholar 

  41. Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG: Primer3–new capabilities and interfaces. Nucleic Acids Res. 2012, 40: e115-10.1093/nar/gks596.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Primer3 standalone program.http://sourceforge.net/projects/primer3/,

Download references

Acknowledgements

Authors are thankful to the National Agricultural Bioinformatics Grid (NABG), under National Agricultural Innovation Project (NAIP), ICAR, New Delhi for providing financial support and the Director, NBFGR, Lucknow for providing necessary facilities to carry out the work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mahender Singh.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

NSN and MS conceived this study. IR, RP & AKP created the work-flow, database, application modules and performed data analyses. SPS and UKS incorporated general information and taxonomy of fishes. IR, RP, NSN, AKP and MS drafted the manuscript. All authors read and approved the final manuscript.

Authors’ original submitted files for images

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article

Nagpure, N.S., Rashid, I., Pati, R. et al. FishMicrosat: a microsatellite database of commercially important fishes and shellfishes of the Indian subcontinent. BMC Genomics 14, 630 (2013). https://doi.org/10.1186/1471-2164-14-630

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/1471-2164-14-630

Keywords