Using Small RNA Deep Sequencing Data to Detect Human Viruses.
Fang WangYu SunJishou RuanRui ChenXin ChenChengjie ChenJan F KreuzeZhangJun FeiXiao ZhuShan GaoPublished in: BioMed research international (2016)
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.
Keyphrases
- hiv positive
- single cell
- diffuse large b cell lymphoma
- antiretroviral therapy
- rna seq
- genome wide
- men who have sex with men
- human immunodeficiency virus
- endothelial cells
- hepatitis c virus
- south africa
- hiv infected
- hiv testing
- epstein barr virus
- electronic health record
- healthcare
- genetic diversity
- big data
- induced apoptosis
- hepatitis b virus
- emergency department
- machine learning
- artificial intelligence
- data analysis
- label free
- real time pcr
- deep learning
- adverse drug
- induced pluripotent stem cells