| Title |
Implementation of Objective PASC-Derived Taxon Demarcation Criteria for Official Classification of Filoviruses
|
|---|---|
| Published in |
Viruses, May 2017
|
| DOI | 10.3390/v9050106 |
| Pubmed ID | |
| Authors |
Yīmíng Bào, Gaya K. Amarasinghe, Christopher F. Basler, Sina Bavari, Alexander Bukreyev, Kartik Chandran, Olga Dolnik, John M. Dye, Hideki Ebihara, Pierre Formenty, Roger Hewson, Gary P. Kobinger, Eric M. Leroy, Elke Mühlberger, Sergey V. Netesov, Jean L. Patterson, Janusz T. Paweska, Sophie J. Smither, Ayato Takada, Jonathan S. Towner, Viktor E. Volchkov, Victoria Wahl-Jensen, Jens H. Kuhn |
| Abstract |
The mononegaviral family Filoviridae has eight members assigned to three genera and seven species. Until now, genus and species demarcation were based on arbitrarily chosen filovirus genome sequence divergence values (≈50% for genera, ≈30% for species) and arbitrarily chosen phenotypic virus or virion characteristics. Here we report filovirus genome sequence-based taxon demarcation criteria using the publicly accessible PAirwise Sequencing Comparison (PASC) tool of the US National Center for Biotechnology Information (Bethesda, MD, USA). Comparison of all available filovirus genomes in GenBank using PASC revealed optimal genus demarcation at the 55-58% sequence diversity threshold range for genera and at the 23-36% sequence diversity threshold range for species. Because these thresholds do not change the current official filovirus classification, these values are now implemented as filovirus taxon demarcation criteria that may solely be used for filovirus classification in case additional data are absent. A near-complete, coding-complete, or complete filovirus genome sequence will now be required to allow official classification of any novel "filovirus." Classification of filoviruses into existing taxa or determining the need for novel taxa is now straightforward and could even become automated using a presented algorithm/flowchart rooted in RefSeq (type) sequences. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 38 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 16% |
| Student > Master | 5 | 13% |
| Student > Bachelor | 4 | 11% |
| Student > Ph. D. Student | 4 | 11% |
| Other | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 14 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 18% |
| Biochemistry, Genetics and Molecular Biology | 4 | 11% |
| Immunology and Microbiology | 3 | 8% |
| Medicine and Dentistry | 3 | 8% |
| Veterinary Science and Veterinary Medicine | 1 | 3% |
| Other | 4 | 11% |
| Unknown | 16 | 42% |