SSRome: an integrated database and pipelines for exploring microsatellites in all organisms
Morad M Mokhtar1, Mohamed A M Atia1
1Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), ARC, Giza, 12619, Egypt.
Nucleic Acids Research
|October 27, 2018
Summary
SSRome is a new web-based database for exploring microsatellites in over 6500 organisms. It addresses previous deficiencies by classifying microsatellites and developing millions of SSR markers for high-throughput research.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Existing microsatellite databases lack genic/non-genic classification and SSR marker development.
- Previous tools failed to comprehensively compare microsatellite motifs across different genomic contexts.
Purpose of the Study:
- To develop SSRome, a user-friendly, comprehensive, and dynamic web-based database for microsatellite exploration.
- To address deficiencies in existing databases by providing genic/non-genic classification and SSR marker development.
- To facilitate high-throughput microsatellite marker development and analysis.
Main Methods:
- Developed SSRome using PHP, HTML, and JavaScript.
- Integrated pipelines for microsatellite mining and analysis across 6533 organisms.
- Included data from NCBI, covering genomes, organelle genomes, and ESTs.
Main Results:
- Identified 158 million microsatellite motifs across all taxa and data types.
- Developed and classified 45.1 million genic and non-genic SSR markers.
- Provided downloadable datasets and user-friendly tools for motif identification, classification, and comparison.
Conclusions:
- SSRome offers a powerful, user-friendly platform for microsatellite research.
- The database facilitates high-throughput development and dissection of SSR markers.
- Researchers can now efficiently explore and utilize microsatellite data for various applications.
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