基因组学技术在病毒鉴定与宿主溯源中的应用

doi:10.17520/biods.2020156

摘要/Abstract

摘要：

基因组学技术, 特别是宏基因组测序在未知病毒的鉴定与溯源中起到了重要作用。相较于传统的病毒分离培养方法, 宏基因组技术可以从混合样本中获得病毒的核酸序列, 极大加速了未知病毒的鉴定与溯源, 在针对高流行性、高致病性的病毒研究中发挥了重要作用。基于宏基因组技术对未知病毒进行鉴定和溯源, 其准确性很大程度上依赖于取样及已知宿主的病毒库的完整性。然而, 当前病毒多样性的基础研究相对薄弱, 病毒的宿主信息则更加匮乏。野生动物和畜禽是人畜共患病致病病毒的重要中间宿主, 构建广泛的动物-病毒关联数据库对于准确、快速地鉴定和预防致病性病毒具有重要意义。本综述以SARS-CoV-2为例, 总结了基因组学技术在病毒的鉴定与溯源上的应用, 并针对当前动物病毒库完整性低的现状, 对构建野生和家养动物携带病毒的关联数据库的可行性提出依据与建议。

关键词: 新冠病毒, 高通量测序, 病毒多样性, 宿主溯源, 病毒进化

Abstract

Genomics technology, especially metagenomic sequencing, has played an important role in identifying and tracing unknown viruses. While classical methods in virus taxonomy rely on phenotypic traits, the metagenomics pipeline assembles new virus genomes from short nucleotide fragments without the need for any a priori reference sequences. This new technology increases the efficiency in identifying viruses and hosts associated with those viruses. This is particularly useful in identifying viruses that can cause epidemics. One current challenge in accomplishing this, is the ability to trace the original and intermediate viral hosts. To do this, a comprehensive virus sequence library characterized by definite host information is needed. Unfortunately, such information is still limited. As wild and stock animals are main sources for pathogenic viruses, an extensive survey of the global virome is vitally important to help identify and prevent zoonotic epidemics. This review summarizes the application of genomics technologies in the identification of viruses and the hosts associated with those viruses, using the outbreak of SARS-CoV-2 as an example. We also address intrinsic drawbacks of current methodologies as well as the incompleteness of available virus libraries. We propose the necessity and feasibility in constructing a comprehensive virus database with host association that emphasizes the diversity of viruses and their interactions with other organisms.

Key words: SARS-CoV-2, high-throughput sequencing, virus diversity, host association, virus evolution

韩本凤, 周欣, 张雪 (2020) 基因组学技术在病毒鉴定与宿主溯源中的应用. 生物多样性, 28, 587-595. DOI: 10.17520/biods.2020156.

Benfeng Han, Xin Zhou, Xue Zhang (2020) Verification of virus identity and host association using genomics technology. Biodiversity Science, 28, 587-595. DOI: 10.17520/biods.2020156.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2020156

https://www.biodiversity-science.net/CN/Y2020/V28/I5/587

图/表 2

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分析方法 Method	作用 Application	常用软件 Software	参考文献 Reference
系统发育树 Phylogenetic trees	分析不同生物间相关性, 通过树状分支可视化生物之间的亲缘关系并推测进化历史 Analyzing the correlation between different organisms, visualizing the relationship between organisms through tree branches and speculating on the evolutionary history	RAxML, phyML, IQ-TREE	Zhou et al, 2020 Wu et al, 2020 Frias-De-Diego et al, 2019 Yuen et al, 2019
重建系统发育中的祖先状态 Reconstructing ancestral state in phylogenies (RASP)	重建祖先在系统发生树上的地理分布, 推断历史生物地理学信息 Inferring historical biogeography through reconstructing ancestral geographic distributions on phylogenetic trees	RASP	Luo et al, 2015 Frias-De-Diego et al, 2019 Yuen et al, 2019
系统发育网络分析 Phylogenetic network analysis	综合一系列系统发育树的可视化结果, 较直观地展示重组等性状冲突事件 Enabling the visualization of a multitude of optimal trees, displaying reorganization and other trait conflict events	Network, SplitsTree	Yu et al, 2020
单倍型网络分析 Haplotype network analysis	用于在群体水平上显示个体基因型之间的关系 An intuitive method used in visualizing relationships between individual genotypes in a population level	PopART	Tang et al, 2020 Leigh & Bryant, 2015
贝叶斯进化分析 Bayesian evolutionary analyses	根据时间进化树建模推断种群发生分歧的时间 Inferring the time when the population diverged based on time evolutionary tree modeling by BEAST	BEAST	Luo et al, 2015 Bouckaert et al, 2014 Suchard et al, 2018
重组分析 Recombination analysis	检验可能存在的重组信号, 揭示重组在基因进化中的作用 Identifying possible recombination signals and revealing the role of recombination in gene evolution	RDP4 Simplot phyML	Wu et al, 2020 Lam et al, 2020

分析方法 Method	作用 Application	常用软件 Software	参考文献 Reference
系统发育树 Phylogenetic trees	分析不同生物间相关性, 通过树状分支可视化生物之间的亲缘关系并推测进化历史 Analyzing the correlation between different organisms, visualizing the relationship between organisms through tree branches and speculating on the evolutionary history	RAxML, phyML, IQ-TREE	Zhou et al, 2020 Wu et al, 2020 Frias-De-Diego et al, 2019 Yuen et al, 2019
重建系统发育中的祖先状态 Reconstructing ancestral state in phylogenies (RASP)	重建祖先在系统发生树上的地理分布, 推断历史生物地理学信息 Inferring historical biogeography through reconstructing ancestral geographic distributions on phylogenetic trees	RASP	Luo et al, 2015 Frias-De-Diego et al, 2019 Yuen et al, 2019
系统发育网络分析 Phylogenetic network analysis	综合一系列系统发育树的可视化结果, 较直观地展示重组等性状冲突事件 Enabling the visualization of a multitude of optimal trees, displaying reorganization and other trait conflict events	Network, SplitsTree	Yu et al, 2020
单倍型网络分析 Haplotype network analysis	用于在群体水平上显示个体基因型之间的关系 An intuitive method used in visualizing relationships between individual genotypes in a population level	PopART	Tang et al, 2020 Leigh & Bryant, 2015
贝叶斯进化分析 Bayesian evolutionary analyses	根据时间进化树建模推断种群发生分歧的时间 Inferring the time when the population diverged based on time evolutionary tree modeling by BEAST	BEAST	Luo et al, 2015 Bouckaert et al, 2014 Suchard et al, 2018
重组分析 Recombination analysis	检验可能存在的重组信号, 揭示重组在基因进化中的作用 Identifying possible recombination signals and revealing the role of recombination in gene evolution	RDP4 Simplot phyML	Wu et al, 2020 Lam et al, 2020

科 Families	种 Species	基因组 Genomes	病毒株 Strains	蛋白 Proteins	缺乏宿主信息比例 Percent without host identification
Arenaviridae	177	4,532	3,012	6,949	23.23%
Caliciviridae	225	52,189	49,073	96,673	28.16%
Coronaviridae	1,043	34,864	28,823	119,573	22.80%
Filoviridae	16	3,577	3,390	22,038	22.53%
Flaviviridae	367	345,546	261,780	877,286	39.36%
Hantaviridae	304	10,189	6,867	10,603	14.02%
Hepeviridae	33	17,838	15,022	19,203	17.95%
Herpesviridae	782	58,371	45,281	300,180	60.18%
Nairoviridae	38	3,669	1,931	3,553	9.92%
Paramyxoviridae	574	50,355	44,898	67,728	24.22%
Peribunyaviridae	183	5,031	2,434	6,367	22.80%
Phasmaviridae	16	1,106	340	1,114	0.27%
Phenuiviridae	215	5,189	2,934	7,133	13.37%
Picornaviridae	1,038	127,336	116,298	346,846	26.91%
Pneumoviridae	17	37,289	33,516	60,235	30.36%
Poxviridae	283	10,444	7,487	125,948	40.87%
Reoviridae	363	107,566	39,985	108,677	15.93%
Rhabdoviridae	530	33,347	26,510	46,761	22.12%
Togaviridae	60	12,800	10,854	46,764	36.25%
总计 Total	6,264	921,238	700,435	2273,631	—

科 Families	种 Species	基因组 Genomes	病毒株 Strains	蛋白 Proteins	缺乏宿主信息比例 Percent without host identification
Arenaviridae	177	4,532	3,012	6,949	23.23%
Caliciviridae	225	52,189	49,073	96,673	28.16%
Coronaviridae	1,043	34,864	28,823	119,573	22.80%
Filoviridae	16	3,577	3,390	22,038	22.53%
Flaviviridae	367	345,546	261,780	877,286	39.36%
Hantaviridae	304	10,189	6,867	10,603	14.02%
Hepeviridae	33	17,838	15,022	19,203	17.95%
Herpesviridae	782	58,371	45,281	300,180	60.18%
Nairoviridae	38	3,669	1,931	3,553	9.92%
Paramyxoviridae	574	50,355	44,898	67,728	24.22%
Peribunyaviridae	183	5,031	2,434	6,367	22.80%
Phasmaviridae	16	1,106	340	1,114	0.27%
Phenuiviridae	215	5,189	2,934	7,133	13.37%
Picornaviridae	1,038	127,336	116,298	346,846	26.91%
Pneumoviridae	17	37,289	33,516	60,235	30.36%
Poxviridae	283	10,444	7,487	125,948	40.87%
Reoviridae	363	107,566	39,985	108,677	15.93%
Rhabdoviridae	530	33,347	26,510	46,761	22.12%
Togaviridae	60	12,800	10,854	46,764	36.25%
总计 Total	6,264	921,238	700,435	2273,631	—