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基于熵的方法鉴定 HPV 基因组中具有系统发生信息的区域

An entropy-based approach for the identification of phylogenetically informative genomic regions of Papillomavirus.

机构信息

Department of Genetics, Center for Biological Sciences, Federal University of Pernambuco, 50670-901 Recife, Pernambuco, Brazil.

出版信息

Infect Genet Evol. 2011 Dec;11(8):2026-33. doi: 10.1016/j.meegid.2011.09.013. Epub 2011 Sep 23.

DOI:10.1016/j.meegid.2011.09.013
PMID:21964599
Abstract

The papillomaviruses form a highly diverse group that infect mammals, birds and reptiles. We know little about their genetic diversity and therefore the evolutionary mechanisms that drive the diversity of these viruses. Genomic sequences of papillomaviruses are highly divergent and so it is important to develop methods that select the most phylogenetic informative sites. This study aimed at making use of a novel approach based on entropy to select suitable genomic regions from which to infer the phylogeny of papillomavirus. Comparative genomic analyzes were performed to assess the genetic variability of each gene of Papillomaviridae family members. Regions with low entropy were selected to reconstruct papillomavirus phylogenetic trees based on four different methods. This methodology allowed us to identify regions that are conserved among papillomaviruses that infect different hosts. This is important because, despite the huge variation among all papillomaviruses genomes, we were able to find regions that are clearly shared among them, presenting low complexity levels of information from which phylogenetic predictions can be made. This approach allowed us to obtain robust topologies from relatively small datasets. The results indicate that the entropy approach can successfully select regions of the genome that are good markers from which to infer phylogenetic relationships, using less computational time, making the estimation of large phylogenies more accessible.

摘要

乳头瘤病毒形成一个高度多样化的群体,感染哺乳动物、鸟类和爬行动物。我们对它们的遗传多样性知之甚少,因此也不知道是什么进化机制导致了这些病毒的多样性。乳头瘤病毒的基因组序列高度变异,因此开发选择最具系统发育信息量的位点的方法非常重要。本研究旨在利用一种基于熵的新方法,从乳头瘤病毒的系统发育推断中选择合适的基因组区域。通过比较基因组分析,评估了乳头瘤病毒科成员的每个基因的遗传变异性。选择熵值较低的区域,基于四种不同的方法构建乳头瘤病毒的系统发育树。这种方法使我们能够确定感染不同宿主的乳头瘤病毒之间保守的区域。这一点很重要,因为尽管所有乳头瘤病毒基因组之间存在巨大差异,但我们能够找到它们之间明显共享的区域,这些区域的信息复杂度较低,可以进行系统发育预测。这种方法使我们能够从相对较小的数据集获得稳健的拓扑结构。结果表明,熵方法可以成功选择基因组中的区域作为推断系统发育关系的良好标记,同时使用较少的计算时间,使大规模系统发育的估计更加容易。

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