Elucidating the Role of Host Long Non-Coding RNA during Viral Infection: Challenges and Paths Forward.
Elucidating the Role of Host Long Non-Coding RNA during Viral Infection: Challenges and Paths Forward.
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DOI：
10.3390/vaccines5040037
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发表时间：
2017-10-20
期刊：
影响因子：
7.8
通讯作者：
Peng X
中科院分区：
文献类型：
--
作者：
Lemler DJ;Brochu HN;Yang F;Harrell EA;Peng X
过去十年的研究清楚地表明，长的非编码RNA(LncRNAs)具有功能。许多lncRNA与免疫和宿主对病毒感染的反应有关，但它们的具体功能在很大程度上仍然难以捉摸。绝大多数的lncRNA是用极其有限的知识来注释的，并且往往在低水平上表达，这使得特别的实验变得困难。感染期间lncRNA表达的变化可以使用深度测序进行系统分析；然而，这通常会产生难以处理的候选lncRNA数量，没有留下明确的前进路径。出于这些原因，尤其重要的是，通过利用多种方法，将LncRNA优先排序为高置信度的“命中”。大规模的扰动研究可能被用来筛选与感兴趣的表型有关的lncRNA，例如对病毒感染的抗性。单细胞转录组测序对混合物中含量较低的细胞类型特异性LncRNAs进行了定量。当结合迭代实验验证时，有效整合正交高通量数据的新计算策略将可能成为阐明lncRNAs在病毒感染过程中的功能作用的驱动因素。这篇综述重点介绍了高通量的新技术，并讨论了综合计算分析的潜力，以简化感染相关lncRNA的识别，并揭示抗病毒治疗的新靶点。
Research over the past decade has clearly shown that long non-coding RNAs (lncRNAs) are functional. Many lncRNAs can be related to immunity and the host response to viral infection, but their specific functions remain largely elusive. The vast majority of lncRNAs are annotated with extremely limited knowledge and tend to be expressed at low levels, making ad hoc experimentation difficult. Changes to lncRNA expression during infection can be systematically profiled using deep sequencing; however, this often produces an intractable number of candidate lncRNAs, leaving no clear path forward. For these reasons, it is especially important to prioritize lncRNAs into high-confidence “hits” by utilizing multiple methodologies. Large scale perturbation studies may be used to screen lncRNAs involved in phenotypes of interest, such as resistance to viral infection. Single cell transcriptome sequencing quantifies cell-type specific lncRNAs that are less abundant in a mixture. When coupled with iterative experimental validations, new computational strategies for efficiently integrating orthogonal high-throughput data will likely be the driver for elucidating the functional role of lncRNAs during viral infection. This review highlights new high-throughput technologies and discusses the potential for integrative computational analysis to streamline the identification of infection-related lncRNAs and unveil novel targets for antiviral therapeutics.
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作者：
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DOI：
10.1016/j.gpb.2015.09.006
发表时间：
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期刊：
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影响因子：
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作者：
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