Tomato (Solanum lycopersicon L.), a new world solanaceous plant is an excellent model for plant genomic research. The genus Solanum is one of the largest angiosperm genera and the genome has 35,000 genes spread over 12 chromosomes and has few high copy number long terminal repeat (LTR) retrotransposons and largely comprised of low-copy DNA [1]. The genome of tomato has been sequenced by The Tomato Genome Consortium in 2012 [1]. A draft sequence of its closest wild relative, i.e. Solanum pimpinellifolium and the potato genome (Solanum tuberosum L.) has also been reported depicting the extent and pattern of similarities and dissimilarities among the three genomes. The tomato genome sequence will have implications on other plant species viz., strawberries, melons, apple etc., which share some characteristics with tomato. Especially common information related to gene and pathway involved in fruit ripening can be potentially applied to other crops also leading to improved fruit quality and reduced cold chain management costs [2].

The leading tomato producing countries of the world are China, USA, India, Turkey, Egypt, and Italy [3]. Globally, USA (23.2%), Germany (16.5%), Russian Federation (9.6%) and United Kingdom (8.3%) are top countries importing tomatoes while Netherlands is the biggest exporter of tomatoes, exporting over 910 346 tons a year and accounting for 20.6% of world export market in tomatoes [4].

Worldwide, tomatoes are an important part of a diverse and balanced diet as a rich source of vitamins, minerals, phenolic antioxidants and anti-oxidant lycopene having anti-cancer properties [5, 6]. A major constraint in tomato production is the loss incurred due to several diseases. Tomato is known to be susceptible to over 200 diseases caused by pathogenic fungi, bacteria, viruses and nematodes [7]. To accelerate conventional plant breeding, Marker Assisted Selection (MAS) with more than 80 resistance genes to major classes of pathogens (fungal, bacterial, virus and nematode) have been used extensively for pyramiding resistance genes [8, 9]. The other essential characteristics for tomato improvement are development of cultivars with broad adaptability, earliness and fruit quality. Over 75,000 accessions of the cultivated and wild species of tomato are maintained in Genebank around the world [10] but relative and absolute differentiation of these accessions need microsatellite (STR) markers. Thus, these bulk whole genome based STR markers are needed for mapping, variety identification and product traceability.

Earlier in silico works for STR mining were not based on whole genome and thus invariably yielded low/very less number of markers, for example just 80 STR were found in entire gene bank search over 2000 sequences. Though the markers were minimum but are highly potential in distinguishing closely related cultivars of tomato [11]. Reported marker density based on in vivo method is relatively less on every chromosome, for example 12^th chromosome has just 37 [12]. For plant variety identification along with degree of admixture, STR is always preferred if they are in multiplex mode (for example, Basmati and non-Basmati rice can be differentiated by 8 plex/ single cocktail based PCR) [13]. Such multiplex designing needs much more number of markers to design multiplex with thermodynamic compatibility, which can be accomplished from our large marker dataset. SGN database is having various classes of markers including STR which are chromosome wise and distance wise based on LOD (Logarithm of the Odds) score [14]. Uniformly distributed markers over genome with an average spacing of 10.0 cM [15] and 1.2 cM (ca. 900 KB) [16] are reported but further higher marker density with average spacing of less than 10 KB has not been reported so far.

Our present work aims at development of such first microsatellite marker database based on whole genome based STR mining which is very user-friendly and freely accessible. Also, the feature of user defined primer designing has great advantage in terms of precise selection from each chromosome, from defined location, size of amplicons for ease of rapid genotyping in simple and low cost agarose gel.

Limited attempt of STR development was reported for example, 12^th chromosome has just 37 markers by earlier in vivo method, but in silico method has extracted 11245 from very same chromosome giving much more marker density, which is highly desirable [12]. Though the genome size range of solanaceae is varying from 0.950 GB (tomato) to 2.70 GB (capsicum) but this family has fixed 12 chromosomes. Although the gene repertoire and gene order of solanaceae species are well conserved, the cause of the genome-size difference is not known [26].

STR plays important role in mapping, trait improvement, variety development, variety identification and product traceability. Traditionally, characterization of varieties is based on phenotypic observation but it is very difficult to distinguish varieties with very similar morphological characteristics and identification of the cultivars accurately is essential for maintaining cultivar integrity and Plant Breeders’ Rights.

Limited studies have been reported in variety identification of tomato using STR DNA markers. In one study, out of 20 STR markers, only 11 were able to discriminate 47 varieties [27] and in another study, 12 markers could differentiate 34 varieties [28]. Studies based on 6000 SNP markers over 93 varieties have demonstrated that SNP based variety differentiation is also possible [29]. However, in such SNP based studies, the genotyping data of "Moneymaker" and "Moneyberg" varieties were completely identical leading to no differentiation at all. So, more STR markers from tomato genome are warranted to address varietal differentiation and product tractability in the food chain. Also, DNA fingerprinting is an appropriate tool to track and trace the tomato supply chain, ensuring not only authenticity and integrity of the products but also the absence of any possible genetic contamination by other species or unwanted components [30–32].

Such use of STR in plant variety identification is well reported in other crops like barley varieties [33], S. tuberosum ssp. tuberosum[34], sugarcane [35], capsicum [36], eggplant [37] and identification of Basmati rice from that of non-Basmati rice [13]. Also, the microsatellite STR markers are the method of first choice to complement the DUS (Distinctness, Uniformity and Stability) testing procedure [38, 39].

Our STR database can be a useful tool in MAS programme of tomato improvement. Such use of STR in crop improvement is already reported in sorghum [40], tagging stem rust resistance gene Sr35 in wheat [41], Fusarium head blight resistance in wheat [42], leaf rust resistance gene Lr35 in wheat [43] and mapping of resistance gene effective against Karnal bunt pathogen of wheat [44]. Wheat improvement programs to enhance leaf rust resistance using STR markers has been attempted [45]. STR markers are also used for introgression programs for trait improvement, for example Soltol QTLs in rice. The location of the Saltol QTL on chromosome 1 and identification of additional QTLs associated with salt tolerance is well identified [46].

The relative density of the tomato whole genome reported in the study is 154 markers per MBp. This is almost in range with Arabidopsis (157 MBp), the other crops reported are with higher number of markers like cucumber (367 MBp), rice (370–490 MBp), popular (485 MBp), grape (487 MBp), sorghum (818 MBp), soybean (1115 MBp), maize (2365 MBp), wheat (1000 MBp) and pigeon pea (833 MBp). Though a general negative correlation between genome size and STR density in plants has been reported [47] but we found distance between markers are not proportion to size of genome thus small genome size has enough marker density for mapping purpose.

TomSatDB is of great use to tomato breeders in molecular breeding. The customization of this tool for search based on chromosome may be used by breeders for mapping of gene by markers. It is likely to be accessed by biologists engaged in research with diverse objectives in the crop primarily to develop molecular markers and also to understand the functional significance of microsatellites in regulating gene expression and genome evolution. The comprehensive options to search for simple and compound microsatellites repeats in the genic regions allow users to explore new avenues of investigations on these repeats. The primer designing for PCR amplification of desired motifs will facilitate studies on mutability, microsatellite abundance etc. Association of microsatellites with a particular disease or phenotype may also be explored. Microsatellite data can also be used to investigate various anomalies using candidate gene approach. This microsatellite database will serve as an important application for extracting information in order to design experiments in new directions elucidating novel roles and functions of microsatellites. The STR markers (>1.4 m) reported here is not only relevant for tomato germplasm management using MAS against 200 biotic and abiotic stress but also to other crops. This database is expected to be of immense use across globe by respective statutory authorities for variety identification and varietal dispute resolution supplementing DUS test and product traceability.

A total of 146602 STR markers are reported for the first time using whole genome in the database. Though we have reported small attempt of in silico validation in our studies but extensive wet lab validation of these markers is warranted. These markers are expected to pave the way of germplasm management over abiotic and biotic stress as well as improvement through molecular breeding, leading to increased tomato productivity in various parts of the world. The marker reported in our database are ready to use for mapping as well as also for variety identification and product traceability, paving the pathway of best use of genomics and computational tool in endeavor of tomato improvement and variety management at global level.

TomSatDB, the tomato microsatellite marker database is freely accessible for research purposes for non-profit and academic organizations at http://cabindb.iasri.res.in/tomsatdb.