Title |
Non-coding RNAs and retroviruses
|
---|---|
Published in |
Retrovirology, February 2018
|
DOI | 10.1186/s12977-018-0403-8 |
Pubmed ID | |
Authors |
Xu Zhang, Xiancai Ma, Shuliang Jing, Hui Zhang, Yijun Zhang |
Abstract |
Retroviruses can cause severe diseases such as cancer and acquired immunodeficiency syndrome. A unique feature in the life cycle of retroviruses is that their RNA genome is reverse transcribed into double-stranded DNA, which then integrates into the host genome to exploit the host machinery for their benefits. The metazoan genome encodes numerous non-coding RNAs (ncRNA), which act as key regulators in essential cellular processes such as antiviral response. The development of next-generation sequencing technology has greatly accelerated the detection of ncRNAs from viruses and their hosts. ncRNAs have been shown to play important roles in the retroviral life cycle and virus-host interactions. Here, we review recent advances in ncRNA studies with special focus on those have changed our understanding of retroviruses or provided novel strategies to treat retrovirus-related diseases. Many ncRNAs such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are involved in the late phase of the retroviral life cycle. However, their roles in the early phase of viral replication merit further investigations. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 17% |
Germany | 1 | 6% |
Australia | 1 | 6% |
India | 1 | 6% |
Taiwan | 1 | 6% |
Norway | 1 | 6% |
United Kingdom | 1 | 6% |
Unknown | 9 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 50% |
Scientists | 6 | 33% |
Science communicators (journalists, bloggers, editors) | 2 | 11% |
Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 81 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 20 | 25% |
Student > Bachelor | 11 | 14% |
Researcher | 7 | 9% |
Student > Master | 7 | 9% |
Student > Postgraduate | 4 | 5% |
Other | 7 | 9% |
Unknown | 25 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 23 | 28% |
Agricultural and Biological Sciences | 13 | 16% |
Immunology and Microbiology | 9 | 11% |
Medicine and Dentistry | 5 | 6% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
Other | 4 | 5% |
Unknown | 25 | 31% |