Instituto de Física, Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, CP 15051, 91501-970 Porto Alegre RS, Brazil.
Institut Curie, PSL Research University, INSERM, U900, 26 rue d'Ulm, F-75005, Paris, France.
PLoS One. 2019 Sep 5;14(9):e0221631. doi: 10.1371/journal.pone.0221631. eCollection 2019.
Dendrograms are a way to represent relationships between organisms. Nowadays, these are inferred based on the comparison of genes or protein sequences by taking into account their differences and similarities. The genetic material of choice for the sequence alignments (all the genes or sets of genes) results in distinct inferred dendrograms. In this work, we evaluate differences between dendrograms reconstructed with different methodologies and for different sets of organisms chosen at random from a much larger set. A statistical analysis is performed to estimate fluctuations between the results obtained from the different methodologies that allows us to validate a systematic approach, based on the comparison of the organisms' metabolic networks for inferring dendrograms. This has the advantage that it allows the comparison of organisms very far away in the evolutionary tree even if they have no known ortholog gene in common. Our results show that dendrograms built using information from metabolic networks are similar to the standard sequence-based dendrograms and can be a complement to them.
树状图是一种表示生物体之间关系的方法。如今，这些都是根据基因或蛋白质序列的比较来推断的，同时考虑它们的差异和相似之处。序列比对（所有基因或基因集）所选择的遗传物质会导致不同的推断树状图。在这项工作中，我们评估了使用不同方法重建的树状图之间的差异，以及从更大的一组中随机选择的不同生物体的树状图。我们进行了统计分析来估计不同方法获得的结果之间的波动，这使得我们可以验证一种基于比较生物体代谢网络来推断树状图的系统方法。这具有允许比较即使在进化树上相距很远的生物体的优点，即使它们没有共同的已知直系同源基因。我们的结果表明，使用代谢网络信息构建的树状图与基于标准序列的树状图相似，并且可以作为其补充。
