Understanding the impact of endogenous viruses on host biology: a combinedcomputational and experimental strategy

该项目的主要目标是利用计算和实验相结合的策略(图1)阐明内源性病毒(ERV)对宿主生物学的影响，重点是三种重要的模式生物--人类、黑猩猩和小鼠。我们将使用HERVd数据库提供的全面ERV注释以及一些其他生物数据库，通过三种替代方法识别功能相关的ERV。首先，我们将基于许多人类种群的变异数据，应用中立性测试来搜索处于正或负选择压力下的人类ERV。其次，我们将使用抗原呈递数据来寻找处于胸腺细胞阴性免疫选择下的ERV家族、个体ERV和特定的ERV基因座。第三，我们将应用比较基因组学方法在不同物种之间寻找进化上保守的ERV基因座。这些多样化的生物信息学方法确定的候选ERV基因座将使用CRISPRi/a技术在转录上被激活和抑制。随后，我们将进行RNA-SEQ分析，并鉴定受ERV激活或抑制影响的差异表达的宿主基因和整个分子网络。在最后一步，识别的候选基因将通过CRISPR在多潜能干细胞中进行调节，并将利用分子生物学技术研究它们的功能作用。该项目预计将产生三种类型的结果。首先，我们将对与ERV相互作用并受其影响的生物途径和分子网络获得新的生物学见解。其次，该项目将对ERV的演变产生新的见解。我们将首次对ERV进行大规模的系统发育研究，确定在特定的分类群和生物特定的基因座上保守的古代元素，并研究它们的基因组背景。第三，我们希望在ERV信息学这一出了名的困难领域取得显著的方法学进步。在该项目过程中，将开发一系列新的生物信息学方法和自动化分析管道，所有产生的数据都将纳入HERVd数据库。

The main goal of the project is to shed light on the impact of endogenous viruses (ERVs) on the host biology using a combined computational and experimental strategy (Figure 1), focusing on three important model organisms – human, chimpanzee, and mouse. We will use the comprehensive ERV annotation available from the HERVd database together with a number of other biological databases to identify functionally relevant ERVs by three alternative approaches. First, we will apply neutrality tests to search for human ERVs which are under positive or negative selection pressure based on the variation data across many human populations. Second, we will use data on antigen presentation to find ERV families, individual ERVs, and specific ERV loci that are under negative immune selection of thymocytes. Third, we will apply comparative genomics approaches to search for evolutionarily conserved ERV loci among different species. Candidate ERV loci identified by these multifarious bioinformatics approaches will be transcriptionally activated and repressed using the CRISPRi/a technology. Subsequently we will conduct RNA-seq analyses and identify differentially expressed host genes and entire molecular networks affected by activation or repression of ERVs. In a final step, the identified candidate genes will be modulated by CRISPR in pluripotent stem cells and their functional role will be investigated by molecular biological techniques. The project is expected to generate three types of outcomes. First, we will obtain novel biological insights into biological pathways and molecular networks which interact with and are affected by ERVs. Second, the project will yield novel insights into ERV evolution. For the first time we will conduct a large-scale phylogenetic study of ERVs, identify ancient elements conserved across specific taxonomic groups as well as organism-specific loci, and study their genomic context. Third, we hope to achieve significant methodological advances in the notoriously difficult area of ERV informatics. A broad spectrum of new bioinformatics approaches and automated analysis pipelines will be developed in the course of the project and all resulting data will be integrated into the HERVd database.