Mining Of Simple Sequence Repeats Research Articles

EST-SSR Mining and Characterization from Aquilaria malaccensis Transcriptome Shotgun Assembly

Aquilaria malaccensis is a member of Thymelaceae family which is one of the main trees producing agarwood compounds in Indonesia and has high economic value. A. malaccensis has Appendix II conservation status due to high exploitation in the nature. One of the several efforts to maintain agarwood production while also maintaining agarwood population is efficient induction by manipulation of the pathway for agarwood formation and using individuals with higher production of agarwood compounds. Selection of superior individuals can be done using molecular markers that are linked to certain genes, including microsatellites or simple sequence repeats (SSR). This study aimed to identify SSRs in the agarwood transcriptome and characterized SSR sites that are linked to genes involved in the synthesis of agarwood compounds. The transcriptome data used was extracted from the NCBI database with accession number GHJS00000000.1. SSR mining was carried out using Krait v.1.4.0 software, then BLASTed with the protein database to analyze the linkage with the related genes. Perfect SSRs were found in 0.37% of the total sequences, and compound SSRs were 10.89%. The abundance of imperfect SSR (107,043) was greater than perfect SSR (31,262), indicating that SSR in the transcriptome had a low mutation rate and the SSR site was more conserved in A. malaccensis. The SSRs that linked to genes related to agarwood synthesis including HMGR, PAL, Mevalonate Kinase, MAPK, Delta-guaiene synthase, Farnesyl pyrophosphate synthase, and Phenylalanine ammonia-lyase. The discovery of SSRs linked to these genes can be used to create molecular markers that can be applied in agarwood producing trees selection.

SATIN: a micro and mini satellite mining tool of total genome and coding regions with analysis of perfect repeats polymorphism in coding regions

BackgroundTandem repeats are specific sequences in genomic DNA repeated in tandem that are present in all organisms. Among the subcategories of TRs we have Satellite repeats, that is divided into macrosatellites, minisatellites, and microsatellites, being the last two of specific interest because they can identify polymorphisms between organisms due to their instability. Currently, most mining tools focus on Simple Sequence Repeats (SSR) mining, and only a few can identify SSRs in the coding regions.ResultsWe developed a microsatellite mining software called SATIN (Micro and Mini SATellite IdentificatioN tool) based on a new sliding window algorithm written in C and Python. It represents a new approach to SSR mining by addressing the limitations of existing tools, particularly in coding region SSR mining. SATIN is available at https://github.com/labgm/SATIN.git. It was shown to be the second fastest for perfect and compound SSR mining. It can identify SSRs from coding regions plus SSRs with motif sizes bigger than 6. Besides the SSR mining, SATIN can also analyze SSRs polymorphism on coding-regions from pre-determined groups, and identify SSRs differentially abundant among them on a per-gene basis. To validate, we analyzed SSRs from two groups of Escherichia coli (K12 and O157) and compared the results with 5 known SSRs from coding regions. SATIN identified all 5 SSRs from 237 genes with at least one SSR on it.ConclusionsThe SATIN is a novel microsatellite search software that utilizes an innovative sliding window technique based on a numerical list for repeat region search to identify perfect, and composite SSRs while generating comprehensible and analyzable outputs. It is a tool capable of using files in fasta or GenBank format as input for microsatellite mining, also being able to identify SSRs present in coding regions for GenBank files. In conclusion, we expect SATIN to help identify potential SSRs to be used as genetic markers.

MegaSSR: a web server for large scale microsatellite identification, classification, and marker development.

Next-generation sequencing technologies have opened new avenues for using genomic data to study and develop molecular markers and improve genetic resources. Simple Sequence Repeats (SSRs) as genetic markers are increasingly used in molecular diversity and molecular breeding programs that require bioinformatics pipelines to analyze the large amounts of data. Therefore, there is an ongoing need for online tools that provide computational resources with minimal effort and maximum efficiency, including automated development of SSR markers. These tools should be flexible, customizable, and able to handle the ever-increasing amount of genomic data. Here we introduce MegaSSR (https://bioinformatics.um6p.ma/MegaSSR), a web server and a standalone pipeline that enables the design of SSR markers in any target genome. MegaSSR allows users to design targeted PCR-based primers for their selected SSR repeats and includes multiple tools that initiate computational pipelines for SSR mining, classification, comparisons, PCR primer design, in silico PCR validation, and statistical visualization. MegaSSR results can be accessed, searched, downloaded, and visualized with user-friendly web-based tools. These tools provide graphs and tables showing various aspects of SSR markers and corresponding PCR primers. MegaSSR will accelerate ongoing research in plant species and assist breeding programs in their efforts to improve current genomic resources.

A review of the endangered mollusks transcriptome under the threatened species initiative of Korea.

Transcriptome studies for conservation of endangered mollusks is a proactive approach towards managing threats and uncertainties facing these species in natural environments. The population of these species is declining due to habitat destruction, illicit wildlife trade, and global climate change. These activities risk the free movement of species across the wild landscape, loss of breeding grounds, and restrictions in displaying the physiological attributes so crucial for faunal welfare. Gastropods face the most negative ecological effects and have been enlisted under Korea's protective species consortium based on their population dynamics in the last few years. Moreover, with the genetic resources restricted for such species, conservation by informed planning is not possible. This review provides insights into the activities under the threatened species initiative of Korea with special reference to the transcriptome assemblies of endangered mollusks. The gastropods such as Ellobium chinense, Aegista chejuensis, Aegista quelpartensis, Incilaria fruhstorferi, Koreanohadra kurodana, Satsuma myomphala, and Clithon retropictus have been represented. Moreover, the transcriptome summary of bivalve Cristaria plicata and Caenogastropoda Charonia lampas sauliae is also discussed. Sequencing, de novo assembly, and annotation identified transcripts or homologs for the species and, based on an understanding of the biochemical and molecular pathways, were ascribed to predictive gene function. Mining for simple sequence repeats from the transcriptome have successfully assisted genetic polymorphism studies. A comparison of the transcriptome scheme of Korean endangered mollusks with the genomic resources of other endangered mollusks have been discussed with homologies and analogies for dictating future research.

Small cardamom genome: development and utilization of microsatellite markers from a draft genome sequence of Elettaria cardamomum Maton.

Small cardamom (Elettaria cardamomum Maton), the queen of spices, is the third most expensive spice in the world after saffron and vanilla, valued highly for its aroma and taste. This perennial herbaceous plant is a native of coastal parts of Southern India and displays a significant amount of morphological diversity. Its genetic potential has not been exploited due to lack of genomic resources limiting our understanding of the genome and important metabolic pathways which give it the economic advantage in the spice industry. Here, we report upon the de novo assembled, draft whole genome sequence of cardamom variety, Njallani Green Gold. We used a hybrid assembly strategy using the reads from the Oxford Nanopore, Illumina and 10x Genomics GemCode sequencing chemistries. The assembled genome length was 1.06 Gb (gigabases) which is close to the estimated genome size of cardamom. More than 75% of the genome was captured in 8000 scaffolds with a N50 of 0.15 Mb. The genome appears to have a high repeat content and 68055 gene models were predicted. The genome is close to Musa species and displays an expansion and contraction in different gene families. The draft assembly was used for in silico mining of simple sequence repeats (SSRs). A total of 2,50,571 SSRs were identified of which 2,18,270 were perfect SSRs and 32,301 were compound SSRs. Among the perfect SSRs, trinucleotides were most abundant (1,25,329) and hexanucleotide repeats appear least (2,380). From the 2,50,571 SSRs mined, 2,27,808 primer pairs were designed based on flanking sequence information. Wet lab validation was performed for 246 SSR loci and based on their amplification profiles, 60 SSR markers were used for diversity analysis of a set of 60 diverse cardamom accessions. The average number of alleles detected per locus were 14.57 with a minimum of 4 and maximum of 30 alleles. Population structure analysis revealed the presence of high degree of admixtures which could primarily be due to cross-pollination prevalent in this species. The SSR markers identified would help in the development of gene or trait-linked markers which can be subsequently used for marker-assisted breeding for crop improvement in cardamom. The information on utilization of the SSR loci for generation of markers has been developed into a public database, 'cardamomSSRdb' that is freely available for use by the cardamom community.

Application of Bioinformatics resources for mining of simple sequence repeats (SSRs) marker in plant genomes: An Overview

In the case of plants, the prediction of simple sequence repeats (SSRs) is important for the purpose of gene mapping, biodiversity study and detection of genes with desired characters. In addition to this, due to their polymorphic nature and distribution throughout the genome, it is considered as an ideal marker in plants. However, the traditional methods for the detection of SSR-based polymorphism cause difficultly. As an alternative method, the bioinformatics approaches have been used extensively in the study of these molecular markers, in a economic way. The next generation sequencing (NGS) techniques generate a huge amount of genomic data which is stored in the public databases in the form of whole genome and EST. This provides the opportunity to implement the bioinformatics tools to predict and annotate the SSR associated with desired gene of the plants. Several computational programs along with the pipelines have been developed to detect the SSR sequences automatically by using the genomic information from the database. In this review, the application and availability of specific bioinformatics resources and the methods of application involved for SSR discovery have been presented by taking suitable examples from the literature.

Genome-wide mining of simple sequence repeats and development of polymorphic SSR markers in Aquilaria malaccensis

Aquilaria malaccensis is one of the economically important tree species distributed in North-east India which produces oleoresinous heartwood known as Agarwood - the most expensive wood in the world. There are limited genomic resources in this species. Therefore, the publicly available whole-genome sequence of Aquilaria agallocha, which is a synonym of A. malaccensis, was utilized for genome-wide mining of Simple Sequence Repeats (SSR) and to develop polymorphic SSR markers. In total 2,53,155 SSRs were identified from the draft genome. Primers were designed for di-nucleotide and tri-nucleotide repeats and screening of 90 such primers have resulted in the identification of 10 polymorphic markers. The present report is the first one for exhaustive identification of SSRs from the draft genome of the species. The SSR markers identified in the present study may be efficient in genomic analyses and useful in the genetic assessment and conservation of A. malaccensis.

A pipeline for effectively developing highly polymorphic simple sequence repeats markers based on multi-sample genomic data.

Simple sequence repeats (SSRs) are widely used genetic markers in ecology, evolution, and conservation even in the genomics era, while a general limitation to their application is the difficulty of developing polymorphic SSR markers. Next‐generation sequencing (NGS) offers the opportunity for the rapid development of SSRs; however, previous studies developing SSRs using genomic data from only one individual need redundant experiments to test the polymorphisms of SSRs. In this study, we designed a pipeline for the rapid development of polymorphic SSR markers from multi‐sample genomic data. We used bioinformatic software to genotype multiple individuals using resequencing data, detected highly polymorphic SSRs prior to experimental validation, significantly improved the efficiency and reduced the experimental effort. The pipeline was successfully applied to a globally threatened species, the brown eared‐pheasant (Crossoptilon mantchuricum), which showed very low genomic diversity. The 20 newly developed SSR markers were highly polymorphic, the average number of alleles was much higher than the genomic average. We also evaluated the effect of the number of individuals and sequencing depth on the SSR mining results, and we found that 10 individuals and ~10X sequencing data were enough to obtain a sufficient number of polymorphic SSRs, even for species with low genetic diversity. Furthermore, the genome assembly of NGS data from the optimal number of individuals and sequencing depth can be used as an alternative reference genome if a high‐quality genome is not available. Our pipeline provided a paradigm for the application of NGS technology to mining and developing molecular markers for ecological and evolutionary studies.

TRANSCRIPTOME SEQUENCING OF LEPISANTHES FRUTICOSA TO DISCOVER SSR MARKERS

Lepisanthes fruticosa (ceri Terengganu) is one of the important underutilized fruit plants with high value of bioactive compounds and pharmacological properties. Current studies have focused mainly on the bioactive compounds which are essential for functional food and pharmaceutical applications. However, studies on the diversity and conservation of L. fruticosa are still scarce since genomic and genetic resources for this plant species are still lacking. In this study, RNA sequencing of L. fruticosa leaf was carried out using Illumina HiSeq to identify potential unigenes and simple sequence repeats (SSRs). A total of 52,657 unigenes were identified from about 91,043,356 million raw sequence reads. Mining of SSRs from these unigenes have predicted a total of 23,958 SSRs which was approximately 45.58% of total unigenes obtained. Dinucleotide repeats motif was the highest (21.48%) and the next were trinucleotide repeats motif (14.65%). A total of 4,620 SSRs ranging from 12 to 116 bp were selected for experimental validation. Bioinformatic analysis via GO and KEGG platforms showed that a total of 1,861 (40.28%) SSR-containing unigenes matched to Gene Ontology (GO) terminology and 48 biochemical pathways. The SSR-containing unigenes of L. fruticosa were involved in various cell functions and a majority of their functions were associated with purine and thiamine metabolism. In addition. A majority of SSR-containing unigenes were involved in organic and heterocylic compounds bindings, indicating an active event of biosynthesis process of secondary metabolites in L. fruticosa. SSR markers obtained from this study provides new genetic information that can be utilized to facilitate future characterization of L. fruticosa accessions at molecular levels.

Mining and validation of novel genotyping-by-sequencing (GBS)-based simple sequence repeats (SSRs) and their application for the estimation of the genetic diversity and population structure of coconuts (Cocos nucifera L.) in Thailand

Coconut (Cocos nucifera L.) is an important economic crop in tropical countries. However, the lack of a complete reference genome and the limitations of usable DNA markers hinder genomic studies and the molecular breeding of coconut. Here, we present the results of simple sequence repeat (SSR) mining from a high-throughput genotyping-by-sequencing (GBS) study of a collection of 38 coconut accessions. A total of 22,748 SSRs with di-, tri-, tetra-, penta- and hexanucleotide repeats of five or more were identified, 2451 of which were defined as polymorphic loci based on locus clustering in 38 coconut accessions, and 315 loci were suitable for the development of SSR markers. One hundred loci were selected, and primer pairs for each SSR locus were designed and validated in 40 coconut accessions. The analysis of 74 polymorphic markers identified between 2 and 9 alleles per locus, with an average of 3.01 alleles. The assessment of the genetic diversity and genetic relationships among the 40 coconut varieties based on the analysis of population structure, principal coordinate analysis (PCoA), and phylogenetic tree analysis using the 74 polymorphic SSR markers revealed three main groups of coconuts in Thailand. The identified SSR loci and SSR markers developed in this study will be useful for the study of coconut diversity and molecular breeding. The SSR mining approach used in this study could be applied to other plant species with a complex genome regardless of the availability of reference genome.

In Silico Mining of Simple Sequence Repeats in Mitochondrial Genomes of Genus Orthotrichum

In Silico Mining of Simple Sequence Repeats in Mitochondrial Genomes of Genus Orthotrichum

Mining of simple sequence repeats (SSRs) loci and development of novel transferability-across EST-SSR markers from de novo transcriptome assembly of Angelica dahurica.

Angelica dahurica is a widely grown plant species with multiple uses, especially in the medical field. However, the frequent introduction of A. dahurica to new areas has made it difficult to distinguish between varieties. Simple sequence repeats (SSRs) detected based on transcriptome analyses are very useful for constructing genetic maps and analyzing genetic diversity. They are also relevant for the molecular marker-assisted breeding of A. dahurica. We identified 33,724 genic SSR loci based on transcriptome sequencing data. A total of 114 primer pairs were designed for the SSR loci and were tested for their specificity and diversity. Ten SSR loci in untranslated regions were ultimately selected. Subsequently, 56 A. dahurica ecotypes collected from different regions were analyzed. The SSR loci comprised 2–8 alleles, with a mean of 5.2 alleles per locus. The polymorphic information content value and Shannon’s information index were 0.6274–0.2702 (average of 0.4091) and 1.3040–0.5618 (average of 0.8475), respectively. Thus, the 10 novel SSRs identified in this study were almost in accordance with Harvey-Weinberg equilibrium and will be useful for analyzing A. dahurica genetic relationships. The results of this study confirm the potential value of transcriptome databases for the development of new SSR markers.

SSR identification and marker development for sago palm based on NGS genome data.

Sago palm (Metroxylon sagu Rottb.) is one of the most productive carbohydrate-producing crops. Unfortunately, only limited information regarding sago palm genetics is available. This study aimed to develop simple sequence repeat (SSR) markers using sago palm NGS genomic data and use these markers to evaluate the genetic diversity of sago palm from Indonesia. De novo assembly of partial sago palm genomic data and subsequent SSR mining identified 29,953 contigs containing 31,659 perfect SSR loci and 31,578 contigs with 33,576 imperfect SSR loci. The perfect SSR loci density was 132.57/Mb, and AG, AAG and AAAT were the most frequent SSR motifs. Five hundred perfect SSR loci were randomly selected and used for designing SSR primers; 93 SSR primer pairs were identified. After synteny analysis using rice genome sequences, 20 primer pairs were validated using 11 sago palm accessions, and seven primers generated polymorphic alleles. Genetic diversity analysis of 41 sago palm accessions from across Indonesia using polymorphic SSR loci indicated the presence of three clusters. These results demonstrated the success of SSR identification and marker development for sago palm based on NGS genome data, which can be further used for assisting sago palm breeding in the future.

Putative Microsatellite DNA Marker-Based Wheat Genomic Resource for Varietal Improvement and Management.

Wheat fulfills 20% of global caloric requirement. World needs 60% more wheat for 9 billion population by 2050 but climate change with increasing temperature is projected to affect wheat productivity adversely. Trait improvement and management of wheat germplasm requires genomic resource. Simple Sequence Repeats (SSRs) being highly polymorphic and ubiquitously distributed in the genome, can be a marker of choice but there is no structured marker database with options to generate primer pairs for genotyping on desired chromosome/physical location. Previously associated markers with different wheat trait are also not available in any database. Limitations of in vitro SSR discovery can be overcome by genome-wide in silico mining of SSR. Triticum aestivum SSR database (TaSSRDb) is an integrated online database with three-tier architecture, developed using PHP and MySQL and accessible at http://webtom.cabgrid.res.in/wheatssr/. For genotyping, Primer3 standalone code computes primers on user request. Chromosome-wise SSR calling for all the three sub genomes along with choice of motif types is provided in addition to the primer generation for desired marker. We report here a database of highest number of SSRs (476,169) from complex, hexaploid wheat genome (~17 GB) along with previously reported 268 SSR markers associated with 11 traits. Highest (116.93 SSRs/Mb) and lowest (74.57 SSRs/Mb) SSR densities were found on 2D and 3A chromosome, respectively. To obtain homozygous locus, e-PCR was done. Such 30 loci were randomly selected for PCR validation in panel of 18 wheat Advance Varietal Trial (AVT) lines. TaSSRDb can be a valuable genomic resource tool for linkage mapping, gene/QTL (Quantitative trait locus) discovery, diversity analysis, traceability and variety identification. Varietal specific profiling and differentiation can supplement DUS (Distinctiveness, Uniformity, and Stability) testing, EDV (Essentially Derived Variety)/IV (Initial Variety) disputes, seed purity and hybrid wheat testing. All these are required in germplasm management as well as also in the endeavor of wheat productivity.

Genome-Wide Analysis of Microsatellites in Alternaria arborescens and Elucidation of the Function of Polyketide Synthase (PksJ).

Microsatellites or simple sequence repeats (SSRs) have been the most widely applied class of molecular markers used in genetic studies, having applications in genetic conservation, population studies, as well as diagnostics of fungi. Mining and analysis of SSRs of the whole genome sequence have been carried out in this study for the fungus Alternaria arborescens causing early blight of tomato and well known for producing mycotoxins like alternariol (AOH), alternariol monomethyl ether (AME), etc. A total of 4097 microsatellites were identified in A. Arborescens genome. Contig 1 was identified as the most SSR-rich region which was further analyzed to correlate the presence of SSRs with different biological processes. A total of 246 putative genes were predicted in this study and KEGG pathway analysis of 155 predicted genes indicated that SSRs can be linked with important metabolic pathways, molecular functioning, signal transduction, and cellular processes. The prediction of fungal mycotoxin inducer gene Polyketide synthase (PksJ) linked with SSR in this study may be a potential candidate participating in oncogenic signal transduction in human. Our study is the first report of PksJ gene in A. arborescens, a precursor of AOH and AME.

WGSSAT: A High-Throughput Computational Pipeline for Mining and Annotation of SSR Markers From Whole Genomes.

Mining and characterization of Simple Sequence Repeat (SSR) markers from whole genomes provide valuable information about biological significance of SSR distribution and also facilitate development of markers for genetic analysis. Whole genome sequencing (WGS)-SSR Annotation Tool (WGSSAT) is a graphical user interface pipeline developed using Java Netbeans and Perl scripts which facilitates in simplifying the process of SSR mining and characterization. WGSSAT takes input in FASTA format and automates the prediction of genes, noncoding RNA (ncRNA), core genes, repeats and SSRs from whole genomes followed by mapping of the predicted SSRs onto a genome (classified according to genes, ncRNA, repeats, exonic, intronic, and core gene region) along with primer identification and mining of cross-species markers. The program also generates a detailed statistical report along with visualization of mapped SSRs, genes, core genes, and RNAs. The features of WGSSAT were demonstrated using Takifugu rubripes data. This yielded a total of 139 057 SSR, out of which 113 703 SSR primer pairs were uniquely amplified in silico onto a T. rubripes (fugu) genome. Out of 113 703 mined SSRs, 81 463 were from coding region (including 4286 exonic and 77 177 intronic), 7 from RNA, 267 from core genes of fugu, whereas 105 641 SSR and 601 SSR primer pairs were uniquely mapped onto the medaka genome. WGSSAT is tested under Ubuntu Linux. The source code, documentation, user manual, example dataset and scripts are available online at https://sourceforge.net/projects/wgssat-nbfgr.

Genome and Transcriptome sequence of Finger millet (Eleusine coracana (L.) Gaertn.) provides insights into drought tolerance and nutraceutical properties

BackgroundFinger millet (Eleusine coracana (L.) Gaertn.) is an important staple food crop widely grown in Africa and South Asia. Among the millets, finger millet has high amount of calcium, methionine, tryptophan, fiber, and sulphur containing amino acids. In addition, it has C4 photosynthetic carbon assimilation mechanism, which helps to utilize water and nitrogen efficiently under hot and arid conditions without severely affecting yield. Therefore, development and utilization of genomic resources for genetic improvement of this crop is immensely useful.ResultsExperimental results from whole genome sequencing and assembling process of ML-365 finger millet cultivar yielded 1196 Mb covering approximately 82% of total estimated genome size. Genome analysis showed the presence of 85,243 genes and one half of the genome is repetitive in nature. The finger millet genome was found to have higher colinearity with foxtail millet and rice as compared to other Poaceae species. Mining of simple sequence repeats (SSRs) yielded abundance of SSRs within the finger millet genome. Functional annotation and mining of transcription factors revealed finger millet genome harbors large number of drought tolerance related genes. Transcriptome analysis of low moisture stress and non-stress samples revealed the identification of several drought-induced candidate genes, which could be used in drought tolerance breeding.ConclusionsThis genome sequencing effort will strengthen plant breeders for allele discovery, genetic mapping, and identification of candidate genes for agronomically important traits. Availability of genomic resources of finger millet will enhance the novel breeding possibilities to address potential challenges of finger millet improvement.

Identification of Expressed Sequence Tag-simple Sequence Repeat Markers from the De Novo Transcriptome Sequence of Red Raspberry (Rubus idaeus L.)

Rubus idaeus has remarkable economic and cultural value. Developing efficient simple sequence repeat (SSR) markers is necessary for the molecular breeding of red raspberry. In this study, SSR mining was performed using the de novo transcriptome sequence of R. idaeus. In total, 14,210 SSR sequences were identified from 11,158 SSR-containing unigenes. In all the SSR sequences, mononucleotide, dinucleotide, and trinucleotide repeats were the most common, and their number and percentage were 1323 (9.31%), 6752 (47.52%), and 4897 (34.46%), respectively. Of the mononucleotide and dinucleotide repeats, A/T, AG/CT, AT/AT, and AC/GT were more abundant and accounted for 9.09%, 37.82%, 6.51%, and 3.14% of the total repeat number, respectively. In the trinucleotide, tetranucleotide, pentanucleotide, and hexanucleotide repeats, the nucleotide (NT) patterns AAG/CTT, AAAG/CTTT, AAAAG/CTTTT, and AAGAGG/CCTCTT were the most frequent, and accounted for 14.11%, 0.38%, 0.57%, and 0.23% of the total SSRs, respectively. Of the 480 SSR-containing unigenes with gene ontology (GO) annotation, the classification results showed that they were mainly involved in binding, catalytic, and transporter molecular functions. Most of the 3441 SSR-containing unigenes with the Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation were involved in the following top five pathways: metabolic, RNA transport, spliceosome, protein processing in the endoplasmic reticulum, and mRNA surveillance. Thirty pairs of primers derived from the red raspberry transcriptome were randomly selected to assess their polymorphism by using 15 red raspberry germplasms, in which the polymorphism information content (PIC) values ranged from 0.50 to 0.86, with a mean of 0.73, thereby indicating a high level of polymorphism. The unweighted pair group method with arithmetic mean clustering results indicated that the thirty pairs of primers could precisely distinguish the germplasms. This study reveals the SSR distribution characteristics of red raspberry and provides a scientific basis for further genetic diversity studies and genetic linkage map construction for this species.

ESAP plus: a web-based server for EST-SSR marker development.

BackgroundSimple sequence repeats (SSRs) have become widely used as molecular markers in plant genetic studies due to their abundance, high allelic variation at each locus and simplicity to analyze using conventional PCR amplification. To study plants with unknown genome sequence, SSR markers from Expressed Sequence Tags (ESTs), which can be obtained from the plant mRNA (converted to cDNA), must be utilized. With the advent of high-throughput sequencing technology, huge EST sequence data have been generated and are now accessible from many public databases. However, SSR marker identification from a large in-house or public EST collection requires a computational pipeline that makes use of several standard bioinformatic tools to design high quality EST-SSR primers. Some of these computational tools are not users friendly and must be tightly integrated with reference genomic databases.ResultsA web-based bioinformatic pipeline, called EST Analysis Pipeline Plus (ESAP Plus), was constructed for assisting researchers to develop SSR markers from a large EST collection. ESAP Plus incorporates several bioinformatic scripts and some useful standard software tools necessary for the four main procedures of EST-SSR marker development, namely 1) pre-processing, 2) clustering and assembly, 3) SSR mining and 4) SSR primer design. The proposed pipeline also provides two alternative steps for reducing EST redundancy and identifying SSR loci. Using public sugarcane ESTs, ESAP Plus automatically executed the aforementioned computational pipeline via a simple web user interface, which was implemented using standard PHP, HTML, CSS and Java scripts. With ESAP Plus, users can upload raw EST data and choose various filtering options and parameters to analyze each of the four main procedures through this web interface. All input EST data and their predicted SSR results will be stored in the ESAP Plus MySQL database. Users will be notified via e-mail when the automatic process is completed and they can download all the results through the web interface.ConclusionsESAP Plus is a comprehensive and convenient web-based bioinformatic tool for SSR marker development. ESAP Plus offers all necessary EST-SSR development processes with various adjustable options that users can easily use to identify SSR markers from a large EST collection. With familiar web interface, users can upload the raw EST using the data submission page and visualize/download the corresponding EST-SSR information from within ESAP Plus. ESAP Plus can handle considerably large EST datasets. This EST-SSR discovery tool can be accessed directly from: http://gbp.kku.ac.th/esap_plus/.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-3328-4) contains supplementary material, which is available to authorized users.

GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing

Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.