Title |
A universal genome sequencing method for rotavirus A from human fecal samples which identifies segment reassortment and multi-genotype mixed infection
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Published in |
BMC Genomics, April 2017
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DOI | 10.1186/s12864-017-3714-6 |
Pubmed ID | |
Authors |
Tran Thi Ngoc Dung, Pham Thanh Duy, October M. Sessions, Uma K. Sangumathi, Voong Vinh Phat, Pham Thi Thanh Tam, Nguyen Thi Nguyen To, Tran My Phuc, Tran Thi Hong Chau, Nguyen Ngoc Minh Chau, Ngoc Nguyen Minh, Guy E. Thwaites, Maia A. Rabaa, Stephen Baker |
Abstract |
Genomic characterization of rotavirus (RoV) has not been adopted at large-scale due to the complexity of obtaining sequences for all 11 segments, particularly when feces are used as starting material. To overcome these limitations, we developed a novel RoV capture and genome sequencing method combining commercial enzyme immunoassay plates and a set of routinely used reagents. Our approach had a 100% success rate, producing >90% genome coverage for diverse RoV present in fecal samples (Ct < 30). This method provides a novel, reproducible and comparatively simple approach for genomic RoV characterization and could be scaled-up for use in global RoV surveillance systems. Current Controlled Trials ISRCTN88101063 . Date of registration: 14/06/2012. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Vietnam | 2 | 50% |
Unknown | 2 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 75% |
Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 56 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 11 | 20% |
Student > Ph. D. Student | 8 | 14% |
Researcher | 7 | 13% |
Student > Bachelor | 3 | 5% |
Student > Postgraduate | 2 | 4% |
Other | 4 | 7% |
Unknown | 21 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 14 | 25% |
Agricultural and Biological Sciences | 11 | 20% |
Medicine and Dentistry | 4 | 7% |
Immunology and Microbiology | 3 | 5% |
Computer Science | 2 | 4% |
Other | 2 | 4% |
Unknown | 20 | 36% |