Feature selection methods for identifying genetic determinants of host species in RNA viruses.
Feature selection methods for identifying genetic determinants of host species in RNA viruses.
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DOI：
10.1371/journal.pcbi.1003254
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发表时间：
2013
影响因子：
4.3
通讯作者：
Ferguson NM
中科院分区：
文献类型：
--
作者：
Aguas R;Ferguson NM
尽管存在环境、社会和生态依赖性，但人畜共患病毒在人群中的出现显然也受到决定跨物种传播潜力的遗传因素的影响。 RNA 病毒构成了一个有趣的案例研究，因为它们的突变率比任何其他病原体高出几个数量级——最近出现的 SARS 和流感就反映了这一点。在这里，我们展示了如何使用特征选择技术按宿主物种可靠地对病毒序列进行分类，并识别病原体基因组数据中至关重要的少数宿主特异性位点。这些位点等位基因的变异性可以转化为特定病原体分离株适应给定宿主的预测概率。我们通过以下方式说明这些方法的威力：1）确定解释人类、蝙蝠和果子狸样本之间 SARS 冠状病毒差异的位点； 2）展示如何容易地识别狂犬病病毒在蝙蝠种群中的跨物种跳跃； 3)从头鉴定可能的功能性流感宿主判别标记。远离用于人类 GWAS 的基因组扫描方法（最终不适合 RNA 病毒的短高度多态性基因组），我们的工作展示了多类机器学习算法在推断与表型变化（例如跨越物种障碍）相关的功能遗传变化方面的力量和潜力。我们发现，即使是病毒家族中关系较远的病毒也具有高度保守的宿主特异性遗传特征。强化宿主适应的适应性景观是如何由宿主系统发育塑造的；并强调RNA病毒在快速扩张和巨大进化压力下的进化轨迹。为此，我们（针对每个数据集）揭示了一组表型特征突变，这些突变被证明在功能上相关，从而为 RNA 病毒之间的表型关系提供了新的见解。这些方法还提供了一个可靠的统计框架，可以推断宿主适应的程度，从而成为研究与新出现的传染病特别相关的宿主转变事件的宝贵工具。这些方法可以作为出现潜力评估的严格工具，特别是在新出现的病毒的快速宿主分类可能比识别假定的功能位点更重要的情况下。
Despite environmental, social and ecological dependencies, emergence of zoonotic viruses in human populations is clearly also affected by genetic factors which determine cross-species transmission potential. RNA viruses pose an interesting case study given their mutation rates are orders of magnitude higher than any other pathogen – as reflected by the recent emergence of SARS and Influenza for example. Here, we show how feature selection techniques can be used to reliably classify viral sequences by host species, and to identify the crucial minority of host-specific sites in pathogen genomic data. The variability in alleles at those sites can be translated into prediction probabilities that a particular pathogen isolate is adapted to a given host. We illustrate the power of these methods by: 1) identifying the sites explaining SARS coronavirus differences between human, bat and palm civet samples; 2) showing how cross species jumps of rabies virus among bat populations can be readily identified; and 3) de novo identification of likely functional influenza host discriminant markers. Moving away from genome scan methods used for human GWAS (ultimately inappropriate for the short highly polymorphic genomes of RNA viruses), our work shows the power and potential of multi-class machine learning algorithms in inferring the functional genetic changes associated with phenotypic change (e.g. crossing a species barrier). We show that even distantly related viruses within a viral family share highly conserved genetic signatures of host specificity; reinforce how fitness landscapes of host adaptation are shaped by host phylogeny; and highlight the evolutionary trajectories of RNA viruses in rapid expansion and under great evolutionary pressure. We do so by (for each dataset) unveiling a set of phenotype characteristic mutations which are shown to be functionally relevant, thus providing new insights into phenotypic relationships between RNA viruses. These methods also provide a solid statistical framework with which the degree of host adaptation can be inferred, thus serving as a valuable tool for studying host transition events with particular relevance for emerging infectious diseases. These methods can then serve as rigorous tools of emergence potential assessment, specifically in scenarios where rapid host classification of newly emerging viruses can be more important than identifying putative functional sites.
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影响因子：
4.8
作者：
Lee RT;Santos CL;de Paiva TM;Cui L;Sirota FL;Eisenhaber F;Maurer-Stroh S
通讯作者：
Maurer-Stroh S
DOI：
10.1098/rspb.2008.0284
发表时间：
2008-07-22
影响因子：
4.7
作者：
Davies, T. Jonathan;Pedersen, Amy B.
通讯作者：
Pedersen, Amy B.
影响因子：
4.3
作者：
Bush WS;Moore JH
通讯作者：
Moore JH
影响因子：
64.8
作者：
Jones KE;Patel NG;Levy MA;Storeygard A;Balk D;Gittleman JL;Daszak P
通讯作者：
Daszak P
DOI：
10.1038/nsb0295-171
发表时间：
1995-02-01
期刊：
NATURE STRUCTURAL BIOLOGY
影响因子：
--
作者：
CASARI, G;SANDER, C;VALENCIA, A
通讯作者：
VALENCIA, A