Title |
Better primer design for metagenomics applications by increasing taxonomic distinguishability
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Published in |
BMC Proceedings, December 2013
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DOI | 10.1186/1753-6561-7-s7-s4 |
Pubmed ID | |
Authors |
Melita Jaric, Jonathan Segal, Eugenia Silva-Herzog, Lisa Schneper, Kalai Mathee, Giri Narasimhan |
Abstract |
Current methods of understanding microbiome composition and structure rely on accurately estimating the number of distinct species and their relative abundance. Most of these methods require an efficient PCR whose forward and reverse primers bind well to the same, large number of identifiable species, and produce amplicons that are unique. It is therefore not surprising that currently used universal primers designed many years ago are not as efficient and fail to bind to recently cataloged species. We propose an automated general method of designing PCR primer pairs that abide by primer design rules and uses current sequence database as input. Since the method is automated, primers can be designed for targeted microbial species or updated as species are added or deleted from the database. In silico experiments and laboratory experiments confirm the efficacy of the newly designed primers for metagenomics applications. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Brazil | 2 | 2% |
Sweden | 1 | 1% |
India | 1 | 1% |
United Kingdom | 1 | 1% |
Philippines | 1 | 1% |
Unknown | 89 | 94% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 21 | 22% |
Student > Ph. D. Student | 19 | 20% |
Researcher | 17 | 18% |
Student > Master | 10 | 11% |
Student > Doctoral Student | 7 | 7% |
Other | 8 | 8% |
Unknown | 13 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 38 | 40% |
Biochemistry, Genetics and Molecular Biology | 19 | 20% |
Environmental Science | 5 | 5% |
Chemistry | 5 | 5% |
Immunology and Microbiology | 5 | 5% |
Other | 10 | 11% |
Unknown | 13 | 14% |