Computational approaches in viral ecology

被引:18
作者
Khot, Varada [1 ]
Strous, Marc [1 ]
Hawley, Alyse K. [1 ]
机构
[1] Univ Calgary, Dept Geosci, Calgary, AB T2N 1N4, Canada
关键词
Bacteriophage-host; Viral diversity; Viral metagenomics; Microbial ecology; Bioinformatics; VIRUSES; PHAGE; EVOLUTIONARY; BACTERIA; IDENTIFICATION; METAGENOMICS; PREDICTION; RESOURCE; SYSTEM; HOSTS;
D O I
10.1016/j.csbj.2020.06.019
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Dynamic virus-host interactions play a critical role in regulating microbial community structure and function. Yet for decades prior to the genomics era, viruses were largely overlooked in microbial ecology research, as only low-throughput culture-based methods of discovering viruses were available. With the advent of metagenomics, culture-independent techniques have provided exciting opportunities to discover and study new viruses. Here, we review recently developed computational methods for identifying viral sequences, exploring viral diversity in environmental samples, and predicting hosts from metagenomic sequence data. Methods to analyze viruses in silico utilize unconventional approaches to tackle challenges unique to viruses, such as vast diversity, mosaic viral genomes, and the lack of universal marker genes. As the field of viral ecology expands exponentially, computational advances have become increasingly important to gain insight into the role viruses in diverse habitats. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
引用
收藏
页码:1605 / 1612
页数:8
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