MitoSatPlant: Mitochondrial Microsatellites Database of Viridiplantae
 
HOME ABOUT DATABASE ADVANCED SEARCH TUTORIAL STATISTICS CONTACT

ABOUT DATABASE

Simple Sequence Repeats (SSRs; Jacob et al. 1991) also known as microsatellites (Litt and Luty 1989) are stretches of DNA sequence consisting of short tandem repeats. Based on the repeating unit SSRs can be categorised into mono- (A)n, di- (GT)n, tri- (CTC)n, tetra- (GATA)n, penta- (ATCGC)n and hexa- (ATTGCC)n nucleotide repeats where n is the number of repeating motif within the SSR locus. Moreover a SSR can be further classified as perfect [without interruptions; (GTG)15], imperfect [interrupted by non repeat nucleotide; (GTG)7G(GTG)8] and compound [two or more SSRs are found adjacent to one another; (GTG)8(AT)16] (Bachmann and Bare 2004). Additionally a compound SSR can be categorized as perfect compound [(GT)n(AG)n] and overlapping compound [overlap of few bases of previous SSR with next SSR; (ACC)n(CT)n].

SSRs are found in prokaryotic and eukaryotic organisms and are widely distributed throughout the genome (both coding and non-coding regions). These are highly polymorphic and can be used as genetic markers. Conventional biotechnological methods for SSR mining are tiresome, lengthy and costly. However computational approaches for data mining of sequences available in biological databases allow quick and inexpensive SSR extraction (Shanker et al. 2007).

Mitochondria, often termed as the power house of cell, are multifunctional organelles and are believed to evolve from eubacteria-like endosymbionts (Gray and Doolittle, 1982). These organelles play key role in ATP synthesis, fatty acid synthesis, Ca2+ signaling and cell death (Zorov et al., 2007; Oberst et al., 2008) and also have important role in deciphering phylogenetic relationship of plants (Shanker, 2013; Shanker, 2013a).

MitoSatPlant is an attempt to provide information of SSRs present in completely sequenced mitochondrial genomes of green plants. The perfect and compound SSRs were mined using Microsatellite Identification Tool (MISA; http://pgrc.ipk-gatersleben.de/misa/) and Imperfect Microsatellite Extractor (IMEx; Mudunuri and Nagarajaram 2007) was used for extracting imperfect SSRs. The minimum length criteria for different repeat types were considered as >=12 for mono-, >=6 for di-, >=4 for tri- and >=3 for tetra-, penta- and hexa- nucleotide repeats. Maximum difference between two compound SSRs was taken as 0. The mismatches allowed for imperfect SSRs were 1 nucleotide for mono-, di- and tri-, 2 for tetra- and penta-, and 3 for hexa- repeats with 10% imperfection. Primer 3 (http://bioinfo.ut.ee/primer3-0.4.0/) with its default parameters was used to design PCR primers for identified SSRs considering 200 base pair of flanking regions. The parsed data was used to develop MitoSatPlant which is an easy to use, interactive relational database of mitochondrial SSRs. User can retrieve information of SSRs frequency according to repeat type (mono-hexa), region [coding, non-coding or coding-non-coding (occurrence of few bases of SSR in coding as well as in non-coding regions or vice-versa)] along with average length of SSRs in an organism, density, primers etc. In case of coding and coding-non-coding SSRs corresponding gene id, protein id, and product are also provided. The displayed data can be downloaded from the link given on top right of web pages. The workflow of the database is shown in Fig 1.

We hope that MitoSatPlant prove to be a useful resource for mitochondrial research.



Fig 1. Workflow of MitoSatPlant.

References

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Jacob HJ, Lindpaintner K, Lincoln SE, Kusumi K, Bunker RK, Mao YP, Ganten D, Dzau VJ, Lander ES (1991) Genetic mapping of a gene causing hypertensive rat. Cell 67: 213-224.
Litt M, Luty JA (1989) A hypervariable microsatellite revealed by in vitro amplification of a dinucleotide repeat within the cardiac muscle actin gene. Am J Hum Genet 44: 397-401.
Mudunuri SB, Nagarajaram HA (2007) IMEx: Imperfect Microsatellite Extractor. Bioinformatics 23: 1181-1187.
Oberst A, Bender C, Green DR (2008) Living with death: the evolution of the mitochondrial pathway of apoptosis in animals. Cell Death Differ. 15: 1139-1146.
Shanker A, Bhargava A, Bajpai R, Singh S, Srivastava S, Sharma V (2007) Bioinformatically mined simple sequence repeats in UniGene of Citrus sinensis. Sci Hort 113: 353-361.
Shanker A (2013) Inference of bryophytes paraphyly using mitochondrial genomes. Archive for Bryology 165: 1-5.
Shanker A (2013a) Combined data from chloroplast and mitochondrial genome sequences showed paraphyly of bryophytes. Archive for Bryology 171: 1-9.
Zorov DB, Isave NK, Plotnikov EY, Zorova LD, Stelmashook EV, Vasileva AK, et al. (2007)The mitochondrion as Janus Bifrons. Biochemistry (Mosc) 72: 1115–26.

Kumar M, Kapil A, Shanker A (2014). Mitochondrion, http:// dx.doi.org/10.1016/j.mito.2014.02.002                                                                                         Site best viewed at 1280x768.