Title |
A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq
|
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Published in |
BMC Genomics, September 2014
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DOI | 10.1186/1471-2164-15-828 |
Pubmed ID | |
Authors |
Grace Logan, Graham L Freimanis, David J King, Begoña Valdazo-González, Katarzyna Bachanek-Bankowska, Nicholas D Sanderson, Nick J Knowles, Donald P King, Eleanor M Cottam |
Abstract |
Next-Generation Sequencing (NGS) is revolutionizing molecular epidemiology by providing new approaches to undertake whole genome sequencing (WGS) in diagnostic settings for a variety of human and veterinary pathogens. Previous sequencing protocols have been subject to biases such as those encountered during PCR amplification and cell culture, or are restricted by the need for large quantities of starting material. We describe here a simple and robust methodology for the generation of whole genome sequences on the Illumina MiSeq. This protocol is specific for foot-and-mouth disease virus (FMDV) or other polyadenylated RNA viruses and circumvents both the use of PCR and the requirement for large amounts of initial template. |
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Geographical breakdown
Country | Count | As % |
---|---|---|
Sweden | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 67% |
Members of the public | 1 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | <1% |
Brazil | 1 | <1% |
Sweden | 1 | <1% |
United Kingdom | 1 | <1% |
Belgium | 1 | <1% |
United States | 1 | <1% |
Unknown | 104 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 30 | 27% |
Student > Ph. D. Student | 21 | 19% |
Student > Master | 17 | 15% |
Student > Doctoral Student | 6 | 5% |
Professor | 5 | 5% |
Other | 15 | 14% |
Unknown | 16 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 43 | 39% |
Biochemistry, Genetics and Molecular Biology | 16 | 15% |
Veterinary Science and Veterinary Medicine | 14 | 13% |
Immunology and Microbiology | 6 | 5% |
Computer Science | 2 | 2% |
Other | 10 | 9% |
Unknown | 19 | 17% |