Engelhardt Institute of Molecular Biology of Russian Academy of Sciences, Vavilov str., 32, Moscow 119334, Russia.
Viruses. 2017 Nov 23;9(12):357. doi: 10.3390/v9120357.
The efficient development of antiviral drugs, including efficient antiviral small interfering RNAs (siRNAs), requires continuous monitoring of the strict correspondence between a drug and the related highly variable viral DNA/RNA target(s). Deep sequencing is able to provide an assessment of both the general target conservation and the frequency of particular mutations in the different target sites. The aim of this study was to develop a reliable bioinformatic pipeline for the analysis of millions of short, deep sequencing reads corresponding to selected highly variable viral sequences that are drug target(s). The suggested bioinformatic pipeline combines the available programs and the ad hoc scripts based on an original algorithm of the search for the conserved targets in the deep sequencing data. We also present the statistical criteria for the threshold of reliable mutation detection and for the assessment of variations between corresponding data sets. These criteria are robust against the possible sequencing errors in the reads. As an example, the bioinformatic pipeline is applied to the study of the conservation of RNA interference (RNAi) targets in human immunodeficiency virus 1 (HIV-1) subtype A. The developed pipeline is freely available to download at the website http://virmut.eimb.ru/. Brief comments and comparisons between VirMut and other pipelines are also presented.
抗病毒药物（包括高效抗病毒小干扰 RNA（siRNA））的有效开发需要不断监测药物与相关高度变异的病毒 DNA/RNA 靶标之间的严格对应关系。深度测序能够评估一般靶标保守性和不同靶标位点特定突变的频率。本研究旨在开发一种可靠的生物信息学管道，用于分析与选定的高度变异病毒序列（即药物靶标）相对应的数百万条短深度测序读取。该建议的生物信息学管道结合了现有的程序和基于深度测序数据中保守目标搜索的原始算法的特定脚本。我们还提出了用于可靠突变检测阈值和评估对应数据集之间差异的统计标准。这些标准不受读取中可能的测序错误的影响。例如，该生物信息学管道应用于研究人类免疫缺陷病毒 1（HIV-1）亚型 A 中 RNA 干扰（RNAi）靶标的保守性。开发的管道可在网站 http://virmut.eimb.ru/ 上免费下载。还提供了对 VirMut 和其他管道的简要评论和比较。
