Title |
TipMT: Identification of PCR-based taxon-specific markers
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Published in |
BMC Bioinformatics, February 2017
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DOI | 10.1186/s12859-017-1485-3 |
Pubmed ID | |
Authors |
Gabriela F. Rodrigues-Luiz, Mariana S. Cardoso, Hugo O. Valdivia, Edward V. Ayala, Célia M. F. Gontijo, Thiago de S. Rodrigues, Ricardo T. Fujiwara, Robson S. Lopes, Daniella C. Bartholomeu |
Abstract |
Molecular genetic markers are one of the most informative and widely used genome features in clinical and environmental diagnostic studies. A polymerase chain reaction (PCR)-based molecular marker is very attractive because it is suitable to high throughput automation and confers high specificity. However, the design of taxon-specific primers may be difficult and time consuming due to the need to identify appropriate genomic regions for annealing primers and to evaluate primer specificity. Here, we report the development of a Tool for Identification of Primers for Multiple Taxa (TipMT), which is a web application to search and design primers for genotyping based on genomic data. The tool identifies and targets single sequence repeats (SSR) or orthologous/taxa-specific genes for genotyping using Multiplex PCR. This pipeline was applied to the genomes of four species of Leishmania (L. amazonensis, L. braziliensis, L. infantum and L. major) and validated by PCR using artificial genomic DNA mixtures of the Leishmania species as templates. This experimental validation demonstrates the reliability of TipMT because amplification profiles showed discrimination of genomic DNA samples from Leishmania species. The TipMT web tool allows for large-scale identification and design of taxon-specific primers and is freely available to the scientific community at http://200.131.37.155/tipMT/ . |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Scientists | 2 | 67% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 43 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 9 | 21% |
Researcher | 8 | 19% |
Student > Bachelor | 5 | 12% |
Student > Ph. D. Student | 5 | 12% |
Student > Doctoral Student | 3 | 7% |
Other | 7 | 16% |
Unknown | 6 | 14% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 11 | 26% |
Biochemistry, Genetics and Molecular Biology | 7 | 16% |
Immunology and Microbiology | 3 | 7% |
Medicine and Dentistry | 3 | 7% |
Engineering | 2 | 5% |
Other | 6 | 14% |
Unknown | 11 | 26% |