Title |
PlantFuncSSR: Integrating First and Next Generation Transcriptomics for Mining of SSR-Functional Domains Markers
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Published in |
Frontiers in Plant Science, June 2016
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DOI | 10.3389/fpls.2016.00878 |
Pubmed ID | |
Authors |
Gaurav Sablok, Antonio J. Pérez-Pulido, Thac Do, Tan Y. Seong, Carlos S. Casimiro-Soriguer, Nicola La Porta, Peter J. Ralph, Andrea Squartini, Antonio Muñoz-Merida, Jennifer A. Harikrishna |
Abstract |
Analysis of repetitive DNA sequence content and divergence among the repetitive functional classes is a well-accepted approach for estimation of inter- and intra-generic differences in plant genomes. Among these elements, microsatellites, or Simple Sequence Repeats (SSRs), have been widely demonstrated as powerful genetic markers for species and varieties discrimination. We present PlantFuncSSRs platform having more than 364 plant species with more than 2 million functional SSRs. They are provided with detailed annotations for easy functional browsing of SSRs and with information on primer pairs and associated functional domains. PlantFuncSSRs can be leveraged to identify functional-based genic variability among the species of interest, which might be of particular interest in developing functional markers in plants. This comprehensive on-line portal unifies mining of SSRs from first and next generation sequencing datasets, corresponding primer pairs and associated in-depth functional annotation such as gene ontology annotation, gene interactions and its identification from reference protein databases. PlantFuncSSRs is freely accessible at: http://www.bioinfocabd.upo.es/plantssr. |
X Demographics
Geographical breakdown
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
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Spain | 1 | 4% |
Netherlands | 1 | 4% |
Unknown | 26 | 93% |
Demographic breakdown
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Researcher | 8 | 29% |
Student > Bachelor | 3 | 11% |
Student > Master | 3 | 11% |
Professor | 2 | 7% |
Student > Ph. D. Student | 2 | 7% |
Other | 4 | 14% |
Unknown | 6 | 21% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 12 | 43% |
Biochemistry, Genetics and Molecular Biology | 5 | 18% |
Computer Science | 2 | 7% |
Unspecified | 1 | 4% |
Social Sciences | 1 | 4% |
Other | 0 | 0% |
Unknown | 7 | 25% |