A new computational method for the detection of horizontal gene transfer events.

A new computational method for the detection of horizontal gene transfer events.
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DOI:
10.1093/nar/gki187
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发表时间:
2005
影响因子:
14.9
通讯作者:
Rigoutsos I
Rigoutsos I
中科院分区:
生物学2区
文献类型:
--
作者:
Tsirigos A;Rigoutsos I

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近年来,随着可用基因组数据量的增加,更容易了解生物体通过横向转移遗传物质增加遗传多样性的程度。这种转移有可能产生极其活跃的基因组,其中很大一部分编码DNA是由外部来源提供的。由于这些水平转移对受体生物体的生态和致病特性的影响,人们不断地寻找能够通过计算确定给定基因组的哪些基因是转移事件的产物的方法。在本文中,我们介绍和讨论了一种新的计算方法,用于确定水平转移,依赖于基因的核苷酸组成,并避免了需要的密码子边界的知识。除了适用于单个基因,该方法可以很容易地扩展到水平转移基因簇的情况。借助对123个古细菌和细菌基因组进行的广泛和精心设计的实验,我们证明了与以前发表的方法相比,新方法在灵敏度方面有显着提高。事实上,与密码子适应指数方法相比,它在区分天然基因和外源基因方面实现了11%至41%的平均相对改进。我们的方法对123个微生物基因组的水平基因转移预测可在线获得。
In recent years, the increase in the amounts of available genomic data has made it easier to appreciate the extent by which organisms increase their genetic diversity through horizontally transferred genetic material. Such transfers have the potential to give rise to extremely dynamic genomes where a significant proportion of their coding DNA has been contributed by external sources. Because of the impact of these horizontal transfers on the ecological and pathogenic character of the recipient organisms, methods are continuously sought that are able to computationally determine which of the genes of a given genome are products of transfer events. In this paper, we introduce and discuss a novel computational method for identifying horizontal transfers that relies on a gene's nucleotide composition and obviates the need for knowledge of codon boundaries. In addition to being applicable to individual genes, the method can be easily extended to the case of clusters of horizontally transferred genes. With the help of an extensive and carefully designed set of experiments on 123 archaeal and bacterial genomes, we demonstrate that the new method exhibits significant improvement in sensitivity when compared to previously published approaches. In fact, it achieves an average relative improvement across genomes of between 11 and 41% compared to the Codon Adaptation Index method in distinguishing native from foreign genes. Our method's horizontal gene transfer predictions for 123 microbial genomes are available online at .
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