Virus-Derived Small RNAs and microRNAs in Health and Disease.

IF 7 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY Annual Review of Biomedical Data Science Pub Date : 2023-08-10 DOI:10.1146/annurev-biodatasci-122220-111429
Vasileios Gouzouasis, Spyros Tastsoglou, Antonis Giannakakis, Artemis G Hatzigeorgiou
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引用次数: 0

Abstract

MicroRNAs (miRNAs) are short noncoding RNAs that can regulate all steps of gene expression (induction, transcription, and translation). Several virus families, primarily double-stranded DNA viruses, encode small RNAs (sRNAs), including miRNAs. These virus-derived miRNAs (v-miRNAs) help the virus evade the host's innate and adaptive immune system and maintain an environment of chronic latent infection. In this review, the functions of the sRNA-mediated virus-host interactions are highlighted, delineating their implication in chronic stress, inflammation, immunopathology, and disease. We provide insights into the latest viral RNA-based research-in silico approaches for functional characterization of v-miRNAs and other RNA types. The latest research can assist toward the identification of therapeutic targets to combat viral infections.

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病毒衍生小rna和微rna在健康和疾病中的作用。
MicroRNAs (miRNAs)是一种短的非编码rna,可以调节基因表达的所有步骤(诱导、转录和翻译)。一些病毒科,主要是双链DNA病毒,编码小rna (sRNAs),包括miRNAs。这些病毒衍生的mirna (v- mirna)帮助病毒逃避宿主的先天和适应性免疫系统,并维持慢性潜伏感染的环境。在这篇综述中,强调了srna介导的病毒-宿主相互作用的功能,描述了它们在慢性应激、炎症、免疫病理和疾病中的作用。我们提供了最新的基于病毒RNA的研究方法,用于v- mirna和其他RNA类型的功能表征。最新的研究有助于确定对抗病毒感染的治疗靶点。
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来源期刊
CiteScore
11.10
自引率
1.70%
发文量
0
期刊介绍: The Annual Review of Biomedical Data Science provides comprehensive expert reviews in biomedical data science, focusing on advanced methods to store, retrieve, analyze, and organize biomedical data and knowledge. The scope of the journal encompasses informatics, computational, artificial intelligence (AI), and statistical approaches to biomedical data, including the sub-fields of bioinformatics, computational biology, biomedical informatics, clinical and clinical research informatics, biostatistics, and imaging informatics. The mission of the journal is to identify both emerging and established areas of biomedical data science, and the leaders in these fields.
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