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基于基因组上下文网络的生命树。

Tree of life based on genome context networks.

作者信息

Ding Guohui, Yu Zhonghao, Zhao Jing, Wang Zhen, Li Yun, Xing Xiaobin, Wang Chuan, Liu Lei, Li Yixue

机构信息

Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People's Republic of China.

出版信息

PLoS One. 2008;3(10):e3357. doi: 10.1371/journal.pone.0003357. Epub 2008 Oct 9.

Abstract

Efforts in phylogenomics have greatly improved our understanding of the backbone tree of life. However, due to the systematic error in sequence data, a sequence-based phylogenomic approach leads to well-resolved but statistically significant incongruence. Thus, independent test of current phylogenetic knowledge is required. Here, we have devised a distance-based strategy to reconstruct a highly resolved backbone tree of life, on the basis of the genome context networks of 195 fully sequenced representative species. Along with strongly supporting the monophylies of three superkingdoms and most taxonomic sub-divisions, the derived tree also suggests some intriguing results, such as high G+C gram positive origin of Bacteria, classification of Symbiobacterium thermophilum and Alcanivorax borkumensis in Firmicutes. Furthermore, simulation analyses indicate that addition of more gene relationships with high accuracy can greatly improve the resolution of the phylogenetic tree. Our results demonstrate the feasibility of the reconstruction of highly resolved phylogenetic tree with extensible gene networks across all three domains of life. This strategy also implies that the relationships between the genes (gene network) can define what kind of species it is.

摘要

系统发育基因组学的研究极大地增进了我们对生命主干树的理解。然而,由于序列数据中的系统误差,基于序列的系统发育基因组学方法会导致分辨率良好但具有统计学显著性的不一致。因此,需要对当前的系统发育知识进行独立检验。在此,我们设计了一种基于距离的策略,以基于195个全测序代表性物种的基因组上下文网络重建一个高分辨率的生命主干树。除了有力支持三个超界和大多数分类亚类的单系性外,推导的树还显示了一些有趣的结果,如细菌的高G+C革兰氏阳性起源、嗜热共生菌和博氏嗜油菌在厚壁菌门中的分类。此外,模拟分析表明,添加更多高精度的基因关系可以大大提高系统发育树的分辨率。我们的结果证明了利用跨生命所有三个域的可扩展基因网络重建高分辨率系统发育树的可行性。该策略还意味着基因之间的关系(基因网络)可以定义它是哪种物种。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/516a/2566592/86f6d01da3b7/pone.0003357.g001.jpg

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