Network-Thinking: Graphs to Analyze Microbial Complexity and Evolution

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• 作者：Eduardo Corel¹ ; ^{eduardo.corel@upmc.fr" class="auth_mail" title="E-mail the corresponding author} ; Philippe Lopez¹ ; Raphaë ; l Mé ; heust¹ ; Eric Bapteste¹
• 关键词：introgression ; gene transfer ; graph theory ; bipartite graph ; symbiosis ; evolution
• 刊名：Trends in Microbiology
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：24
• 期：3
• 页码：224-237
• 全文大小：2776 K

文摘

The tree model and tree-based methods have played a major, fruitful role in evolutionary studies. However, with the increasing realization of the quantitative and qualitative importance of reticulate evolutionary processes, affecting all levels of biological organization, complementary network-based models and methods are now flourishing, inviting evolutionary biology to experience a network-thinking era. We show how relatively recent comers in this field of study, that is, sequence-similarity networks, genome networks, and gene families–genomes bipartite graphs, already allow for a significantly enhanced usage of molecular datasets in comparative studies. Analyses of these networks provide tools for tackling a multitude of complex phenomena, including the evolution of gene transfer, composite genes and genomes, evolutionary transitions, and holobionts.