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利用多个系统发育树追踪禽流感(H5N1)的地理传播情况。

Tracking the geographical spread of avian influenza (H5N1) with multiple phylogenetic trees.

作者信息

Hovmöller Rasmus, Alexandrov Boyan, Hardman Jori, Janies Daniel

机构信息

Mathematical Biosciences Institute, The Ohio State University, Columbus, OH, USA.

Department of Biomedical Informatics, The Ohio State University, Columbus, OH, USA.

出版信息

Cladistics. 2010 Feb;26(1):1-13. doi: 10.1111/j.1096-0031.2009.00297.x. Epub 2009 Nov 13.

Abstract

Avian influenza (H5N1) has been of great social and economic importance since it first infected humans in Hong Kong in 1997. A highly pathogenic strain has spread from China and has killed humans in east Asia, west Africa, south Asia, and the Middle East. Recently, several molecular phylogenetic studies have focused on the relationships of various clades of H5N1 and their spread over time, space, and various hosts. These studies examining the geographical spread of H5N1 have based their conclusions on a single tree. This tree often results from the analysis of the genomic segment coding for the haemagglutinin (HA) or neuraminidase (NA) proteins and a limited sample of viral isolates. Here we present the first study using multiple candidate trees to estimate geographical transmission routes of H5N1. In addition, we use all high-quality HA and NA sequences available to the public as of June 2008. We estimated geographical transmission routes of H5N1 by optimizing multistate characters with states representing different geographical regions over a pool of presumed minimum-length trees. We also developed means to visualize our results in Keyhole Markup Language (KML) for virtual globes. We provide these methods as a web application entitled "Routemap" (http://routemap.osu.edu). The resulting visualizations are akin to airline route maps but they depict the routes of spread of viral lineages. We compare our results with the results of previous studies. We focus on the sensitivity of results to sampling of tree space, character coding schemes, optimization methods, and taxon sampling. In conclusion, we find that using one tree and a single character optimization method will ignore many of the transmission routes indicated by genetic sequence and geographical data. © The Willi Hennig Society 2009.

摘要

自1997年在香港首次感染人类以来,禽流感(H5N1)已具有重大的社会和经济影响。一种高致病性毒株已从中国传播开来,并在东亚、西非、南亚和中东导致人类死亡。最近,一些分子系统发育研究聚焦于H5N1各进化枝之间的关系及其在时间、空间和不同宿主中的传播情况。这些研究在考察H5N1的地理传播时,其结论是基于单一的系统树得出的。这棵树通常源于对编码血凝素(HA)或神经氨酸酶(NA)蛋白的基因组片段以及有限数量病毒分离株样本的分析。在此,我们首次开展研究,使用多个候选系统树来估计H5N1的地理传播路径。此外,我们使用了截至2008年6月向公众公开的所有高质量HA和NA序列。我们通过在一组假定的最小长度系统树上优化以不同地理区域为状态的多状态特征,来估计H5N1的地理传播路径。我们还开发了以键孔标记语言(KML)在虚拟地球仪上可视化结果的方法。我们将这些方法作为一个名为“路线图”(http://routemap.osu.edu)的网络应用程序提供。最终的可视化结果类似于航线图,但描绘的是病毒谱系的传播路径。我们将我们的结果与先前研究的结果进行比较。我们关注结果对系统树空间采样、特征编码方案、优化方法和分类单元采样的敏感性。总之,我们发现使用一棵系统树和单一的特征优化方法会忽略遗传序列和地理数据所显示的许多传播路径。©威利·亨尼希协会2009年。

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