Title |
A complex virome unveiled by deep sequencing analysis of RNAs from a French Pinot Noir grapevine exhibiting strong leafroll symptoms.
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Published in |
Archives of Virology, July 2018
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DOI | 10.1007/s00705-018-3949-9 |
Pubmed ID | |
Authors |
Monique Beuve, Jean-Michel Hily, Antoine Alliaume, Catherine Reinbold, Jean Le Maguet, Thierry Candresse, Etienne Herrbach, Olivier Lemaire |
Abstract |
We have characterized the virome of a grapevine Pinot Noir accession (P70) that displayed, over the year, very stable and strong leafroll symptoms. For this, we have used two extraction methods (dsRNA and total RNA) coupled with the high throughput sequencing (HTS) Illumina technique. While a great disparity in viral sequences were observed, both approaches gave similar results, revealing a very complex infection status. Five virus and viroid isolates [Grapevine leafroll-associated viruse-1 (GLRaV-1), Grapevine virus A (GVA), Grapevine rupestris stem pitting-associated virus (GRSPaV), Hop stunt viroid (HSVd) and Grapevine yellow speckle viroid 1 (GYSVd1)] were detected in P70 with a grand total of eleven variants being identified and de novo assembled. A comparison between both extraction methods regarding their power to detect viruses and the ease of genome assembly is also provided. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
South Africa | 1 | 20% |
France | 1 | 20% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 80% |
Science communicators (journalists, bloggers, editors) | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 27 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 6 | 22% |
Student > Ph. D. Student | 3 | 11% |
Student > Doctoral Student | 3 | 11% |
Student > Bachelor | 2 | 7% |
Student > Master | 2 | 7% |
Other | 5 | 19% |
Unknown | 6 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 10 | 37% |
Biochemistry, Genetics and Molecular Biology | 7 | 26% |
Nursing and Health Professions | 1 | 4% |
Computer Science | 1 | 4% |
Immunology and Microbiology | 1 | 4% |
Other | 0 | 0% |
Unknown | 7 | 26% |