Using Small RNA Deep Sequencing Data to Detect Human Viruses
Joint Authors
Gao, Shan
Ruan, Jishou
Wang, Fang
Sun, Yu
Chen, Rui
Chen, Xin
Chen, Chengjie
Kreuze, Jan F.
Fei, ZhangJun
Zhu, Xiao
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-15
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Small RNA sequencing (sRNA-seq) can be used to detect viruses in infected hosts without the necessity to have any prior knowledge or specialized sample preparation.
The sRNA-seq method was initially used for viral detection and identification in plants and then in invertebrates and fungi.
However, it is still controversial to use sRNA-seq in the detection of mammalian or human viruses.
In this study, we used 931 sRNA-seq runs of data from the NCBI SRA database to detect and identify viruses in human cells or tissues, particularly from some clinical samples.
Six viruses including HPV-18, HBV, HCV, HIV-1, SMRV, and EBV were detected from 36 runs of data.
Four viruses were consistent with the annotations from the previous studies.
HIV-1 was found in clinical samples without the HIV-positive reports, and SMRV was found in Diffuse Large B-Cell Lymphoma cells for the first time.
In conclusion, these results suggest the sRNA-seq can be used to detect viruses in mammals and humans.
American Psychological Association (APA)
Wang, Fang& Sun, Yu& Ruan, Jishou& Chen, Rui& Chen, Xin& Chen, Chengjie…[et al.]. 2016. Using Small RNA Deep Sequencing Data to Detect Human Viruses. BioMed Research International،Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1097115
Modern Language Association (MLA)
Wang, Fang…[et al.]. Using Small RNA Deep Sequencing Data to Detect Human Viruses. BioMed Research International No. 2016 (2016), pp.1-9.
https://search.emarefa.net/detail/BIM-1097115
American Medical Association (AMA)
Wang, Fang& Sun, Yu& Ruan, Jishou& Chen, Rui& Chen, Xin& Chen, Chengjie…[et al.]. Using Small RNA Deep Sequencing Data to Detect Human Viruses. BioMed Research International. 2016. Vol. 2016, no. 2016, pp.1-9.
https://search.emarefa.net/detail/BIM-1097115
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1097115