virMine: automated detection of viral sequences from complex metagenomic samples

virMine: automated detection of viral sequences from complex metagenomic samples
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DOI:
10.7717/peerj.6695
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发表时间:
2019-04-10
期刊:
影响因子:
2.7
通讯作者:
Putonti, Catherine
Putonti, Catherine
中科院分区:
生物学3区
文献类型:
--
作者:
Garretto, Andrea;Hatzopoulos, Thomas;Putonti, Catherine

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宏基因组学使得能够对来自无数不同环境的病毒群落进行测序。病毒宏基因组研究通常发现与已知编码区或基因组没有可识别同源性的序列。尽管如此,完整的病毒基因组已经直接从复杂的社区宏基因组构建,通常通过繁琐的人工策展。为了解决这个问题,我们开发了软件工具virMine,以从代表病毒或混合(病毒和细菌)群落的原始读段中识别病毒基因组。virMine自动化序列读取质量控制、组装和注释。研究人员可以很容易地改进他们对特定研究系统和/或感兴趣的功能的搜索。与通常依赖于病毒特征序列识别的其他病毒基因组检测工具相比,virMine不受公共数据库中病毒多样性代表性不足的限制。相反,病毒基因组是通过迭代方法识别的,首先省略非病毒序列。因此,可以检测到先前表征的病毒和新物种的亲属,包括真核病毒和噬菌体。在这里,我们介绍了virMine及其对合成群落的分析,以及来自三个明显不同环境的宏基因组数据集:肠道微生物群,尿液微生物群和淡水病毒组。几个新的病毒基因组被确定和注释,从而有助于我们了解这三种环境中的病毒遗传多样性。
Metagenomics has enabled sequencing of viral communities from a myriad of different environments. Viral metagenomic studies routinely uncover sequences with no recognizable homology to known coding regions or genomes. Nevertheless, complete viral genomes have been constructed directly from complex community metagenomes, often through tedious manual curation. To address this, we developed the software tool virMine to identify viral genomes from raw reads representative of viral or mixed (viral and bacterial) communities. virMine automates sequence read quality control, assembly, and annotation. Researchers can easily refine their search for a specific study system and/or feature(s) of interest. In contrast to other viral genome detection tools that often rely on the recognition of viral signature sequences, virMine is not restricted by the insufficient representation of viral diversity in public data repositories. Rather, viral genomes are identified through an iterative approach, first omitting non-viral sequences. Thus, both relatives of previously characterized viruses and novel species can be detected, including both eukaryotic viruses and bacteriophages. Here we present virMine and its analysis of synthetic communities as well as metagenomic data sets from three distinctly different environments: the gut microbiota, the urinary microbiota, and freshwater viromes. Several new viral genomes were identified and annotated, thus contributing to our understanding of viral genetic diversity in these three environments.