| Chapter title |
Detection of Plant Viruses in Natural Environments by Using RNA-Seq
|
|---|---|
| Chapter number | 8 |
| Book title |
Plant Virology Protocols
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-1743-3_8 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-1742-6, 978-1-4939-1743-3
|
| Authors |
Atsushi J Nagano, Mie N Honjo, Motohiro Mihara, Masanao Sato, Hiroshi Kudoh, Atsushi J. Nagano, Mie N. Honjo, Nagano, Atsushi J., Honjo, Mie N., Mihara, Motohiro, Sato, Masanao, Kudoh, Hiroshi |
| Abstract |
Sequencing of RNA by next generation sequencers, RNA-Seq, is revolutionizing virus detection. In addition to the unbiased detection of various viruses from wild plants in natural environments, RNA-Seq also allows for the parallel collection of host plant transcriptome data. Host transcriptome data are highly valuable for studying the responses of hosts to viral infections, as well as viral host manipulation. When detecting viruses using RNA-Seq, it is critical to choose appropriate methods for the removal of rRNA from total RNA. Although viruses with polyadenylated genomes can be detected by RNA-Seq following mRNA purification using oligo-dT beads, viruses with non-polyadenylated genomes are not effectively detected. However, such viruses can be detected by RNA-Seq using the rRNA selective depression method. The high-throughput and cost-effective method of RNA-Seq library preparation which is described here allows us to detect a broad range of viruses in wild plants. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 50% |
| India | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 53 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 18% |
| Student > Bachelor | 9 | 16% |
| Student > Doctoral Student | 8 | 15% |
| Student > Ph. D. Student | 7 | 13% |
| Other | 4 | 7% |
| Other | 12 | 22% |
| Unknown | 5 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 30 | 55% |
| Biochemistry, Genetics and Molecular Biology | 8 | 15% |
| Computer Science | 2 | 4% |
| Social Sciences | 2 | 4% |
| Chemical Engineering | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 8 | 15% |