Dataset Information

GMATo: A novel tool for the identification and analysis of microsatellites in large genomes.

ABSTRACT:

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Simple Sequence Repeats (SSR), also called microsatellite, is very useful for genetic marker development and genome application. The increasing whole sequences of more and more large genomes provide sources for SSR mining in silico. However currently existing SSR mining tools can't process large genomes efficiently and generate no or poor statistics. Genome-wide Microsatellite Analyzing Tool (GMATo) is a novel tool for SSR mining and statistics at genome aspects. It is faster and more accurate than existed tools SSR Locator and MISA. If a DNA sequence was too long, it was chunked to short segments at several Mb followed by motifs generation and searching using Perl powerful pattern match function. Matched loci data from each chunk were then merged to produce final SSR loci information. Only one input file is required which contains raw fasta DNA sequences and output files in tabular format list all SSR loci information and statistical distribution at four classifications. GMATo was programmed in Java and Perl with both graphic and command line interface, either executable alone in platform independent manner with full parameters control. Software GMATo is a powerful tool for complete SSR characterization in genomes at any size.

Availability

The soft GMATo is freely available at http://sourceforge.net/projects/gmato/files/?source=navbar or on contact.

SUBMITTER: Wang X

PROVIDER: S-EPMC3705631 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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GMATo: A novel tool for the identification and analysis of microsatellites in large genomes.

Wang Xuewen X Lu Peng P Luo Zhaopeng Z

Bioinformation 20130608 10

<h4>Unlabelled</h4>Simple Sequence Repeats (SSR), also called microsatellite, is very useful for genetic marker development and genome application. The increasing whole sequences of more and more large genomes provide sources for SSR mining in silico. However currently existing SSR mining tools can't process large genomes efficiently and generate no or poor statistics. Genome-wide Microsatellite Analyzing Tool (GMATo) is a novel tool for SSR mining and statistics at genome aspects. It is faster ...[more]

PMID: 23861572

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Project description:BACKGROUND: Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last decade, although testing putative SSR markers still is time consuming and expensive. In many species only a relatively small percentage of SSR markers turn out to be polymorphic. This is particularly true for markers derived from expressed sequence tags (ESTs). In EST databases a large redundancy of sequences is present, which may contain information on length-polymorphisms in the SSR they contain, and whether they have been derived from heterozygotes or from different genotypes. Up to now, although a number of programs have been developed to identify SSRs in EST sequences, no software can detect putatively polymorphic SSRs. RESULTS: We have developed PolySSR, a new pipeline to identify polymorphic SSRs rather than just SSRs. Sequence information is obtained from public EST databases derived from heterozygous individuals and/or at least two different genotypes. The pipeline includes PCR-primer design for the putatively polymorphic SSR markers, taking into account Single Nucleotide Polymorphisms (SNPs) in the flanking regions, thereby improving the success rate of the potential markers. A large number of polymorphic SSRs were identified using publicly available EST sequences of potato, tomato, rice, Arabidopsis, Brassica and chicken.The SSRs obtained were divided into long and short based on the number of times the motif was repeated. Surprisingly, the frequency of polymorphic SSRs was much higher in the short SSRs. CONCLUSION: PolySSR is a very effective tool to identify polymorphic SSRs. Using PolySSR, several hundred putative markers were developed and stored in a searchable database. Validation experiments showed that almost all markers that were indicated as putatively polymorphic by polySSR were indeed polymorphic. This greatly improves the efficiency of marker development, especially in species where there are low levels of polymorphism, like tomato. When combined with the new sequencing technologies PolySSR will have a big impact on the development of polymorphic SSRs in any species.PolySSR and the polymorphic SSR marker database are available from http://www.bioinformatics.nl/tools/polyssr/.

Project description:Novel sequences are DNA sequences present in an individual's genome but absent in the human reference assembly. They are predicted to be biologically important, both individual and population specific, and consistent with the known human migration paths. Recent works have shown that an average person harbors 2-5 Mb of such sequences and estimated that the human pan-genome contains as high as 19-40 Mb of novel sequences. To identify them in a de novo genome assembly, some existing sequence aligners have been used but no computational method has been specifically proposed for this task. In this work, we developed NSIT (Novel Sequence Identification Tool), a software that can accurately and efficiently identify novel sequences in an individual's de novo whole genome assembly. We identified and characterized 1.1 Mb, 1.2 Mb, and 1.0 Mb of novel sequences in NA18507 (African), YH (Asian), and NA12878 (European) de novo genome assemblies, respectively. Our results show very high concordance with the previous work using the respective reference assembly. In addition, our results using the latest human reference assembly suggest that the amount of novel sequences per individual may not be as high as previously reported. We additionally developed a graphical viewer for comparisons of novel sequence contents. The viewer also helped in identifying sequence contamination; we found 130 kb of Epstein-Barr virus sequence in the previously published NA18507 novel sequences as well as 287 kb of zebrafish repeats in NA12878 de novo assembly. NSIT requires [Formula: see text]2GB of RAM and 1.5-2 hrs on a commodity desktop. The program is applicable to input assemblies with varying contig/scaffold sizes, ranging from 100 bp to as high as 50 Mb. It works in both 32-bit and 64-bit systems and outperforms, by large margins, other fast sequence aligners previously applied to this task. To our knowledge, NSIT is the first software designed specifically for novel sequence identification in a de novo human genome assembly.

Dataset Information

GMATo: A novel tool for the identification and analysis of microsatellites in large genomes.

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Availability

Publications

GMATo: A novel tool for the identification and analysis of microsatellites in large genomes.

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