一个更准确和有效的全基因组系统发育

P. Chan, T. Lam, S. Yiu
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引用次数: 6

摘要

为了重建一组给定物种的系统发育,以前的大多数方法都是基于从相应基因组中的保守区域(或基因)子集中获得的相似性信息。在某些情况下,所选择的区域可能不能反映物种的进化史,并且可能太受限制而无法区分物种。人们普遍认为,如果考虑到整个基因组,推断可能会更准确。利用完整基因组的现有最佳解决方案是由Henz等人提出的。13他们可以在170个CPU小时内构建91个原核生物基因组的系统发育,准确率约为70%(基于非琐碎分裂的测量),而使用全基因组的其他方法只能处理不超过20个物种。请注意,Henz等人使用BLASTN测量物种之间的距离,BLASTN主要不是为全基因组比对而设计的。此外,他们的方法不具有可扩展性,例如,为NCBI公布的所有230个原核基因组构建系统发育可能需要超过1000个CPU小时。此外,我们发现非琐碎的分裂只是系统发育准确性的一个粗略指标。在本文中,我们提出以下几点建议。(1)为了评估系统发育相对于模型答案的质量,我们建议使用最大一致子树的概念,因为它可以捕获系统发育的结构。(2)我们建议使用全基因组比对软件(如MUMmer)来测量物种之间的距离,并推导出一种有效的方法来生成这些距离。通过对真实数据集的实验,我们发现我们的方法比Henz等人的方法更准确,更具可扩展性。我们可以在2个CPU小时内(比他们的方法快80倍以上)以超过20%的准确率(相对于两种评估方法)为同一组91个基因组构建系统发育树。此外,我们的方法具有可扩展性,可以在9.5个CPU小时内以高达85%的准确率构建230个原核基因组的系统发育。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A More Accurate and Efficient Whole Genome Phylogeny
To reconstruct a phylogeny for a given set of species, most of the previous approaches are based on the similarity information derived from a subset of conserved regions (or genes) in the corresponding genomes. In some cases, the regions chosen may not reflect the evolutionary history of the species and may be too restricted to differentiate the species. It is generally believed that the inference could be more accurate if whole genomes are being considered. The best existing solution that makes use of complete genomes was proposed by Henz et al.13 They can construct a phylogeny for 91 prokaryotic genomes in 170 CPU hours with an accuracy of about 70% (based on the measurement of non-trivial splits) while other approaches that use whole genomes can only deal with no more than 20 species. Note that Henz et al. measure the distance between the species using BLASTN which is not primarily designed for whole genome alignment. Also, their approach is not scalable, for example, it probably takes over 1000 CPU hours to construct a phylogeny for all 230 prokaryotic genomes published by NCBI. In addition, we found that non-trivial splits is only a rough indicator of the accuracy of the phylogeny. In this paper, we propose the followings. (1) To evaluate the quality of a phylogeny with respect to a model answer, we suggest to use the concept of the maximum agreement subtree as it can capture the structure of the phylogeny. (2) We propose to use whole genome alignment software (such as MUMmer) to measure the distances between the species and derive an efficient approach to generate these distances. From the experiments on real data sets, we found that our approach is more accurate and more scalable than Henz et al.’s approach. We can construct a phylogenetic tree for the same set of 91 genomes with an accuracy more than 20% higher (with respect to both evaluation measures) in 2 CPU hours (more than 80 times faster than their approach). Also, our approach is scalable and can construct a phylogeny for 230 prokaryotic genomes with accuracy as high as 85% in only 9.5 CPU hours.
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